Celebrating Women in Analytics 2023!

In a normal day, what kinds of data / analytics activities are you involved in?

Current and previous roles have included data visualisation using Tableau, strategy and roadmaps, planning and Tableau Server administration and support.

What are the biggest challenges you face?

Managing changes in upstream source systems, which flow downstream to data warehouses and visualisations. Can be extremely challenging to understand the changes, assess the impact, and iterate data and visualisation layers so as to minimise the downstream impact on our audience.

What would be the proudest or most enjoyable moment in your analytics career?

Working on the BI solution for the London 2012 Olympics and seeing our stats on the BBC

What advice would you give to a woman wanting to get into the analytics industry?

Analytics is a great option for a very rewarding career, and I would highly encourage any women who are looking to get into these fields. I am lucky to wake up each day and enjoy what I do! Recently there are many more opportunities for analytics jobs to be remote or hybrid, so you can fit your job amongst the other responsibilities in life - such as family.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

Data visualisation is a wonderful mix of STEM (what is the data telling you) and art (how do you communicate these insights to your audience), and I think ML and AI will enhance both of these aspects and enable us to engage our audiences more.

In a normal day, what kinds of data / analytics activities are you involved in?

Data modelling & Management, Data governance, Data Engineering and Data Visualisation are the core activities that we do as D&A team at JLL. 

I have been hands-on on the tools for 17+ years now  but my as of today my day-to-day job demands more of relationship management with executive stakeholders. Both to share highlights of the work my team are delivering to help them achieve their business outcomes, and/or understanding their business goals and problems to identify opportunities to add value with data and analytics.

What are the biggest challenges you face?

1. Data quality /Data collection gaps

2. Data Literacy / User Adoption

3. Quantifying value / realisation of ROI that we bring as D&A team

What would be the proudest or most enjoyable moment in your analytics career?

I was shortlisted as "Data Leader of the year" award in 2022. I am very proud of the recognition received and the fact that I am representing my organisation for the work done by our team. This is not just  a single most enjoyable moment but I enjoy every aspect of my job which usually usually entails guiding the smart technical people to develop some really impactful insights with a quantifiable outcome. Moreover, I love getting the business users excited about the new possibilities. And finally when we see our work helping the business progress toward their goals and priorities by giving them ability to identify the actions required is incredibly rewarding.

What advice would you give to a woman wanting to get into the analytics industry?

My advice for anyone looking to get into anything new is to take the first step and do it.

Women are naturally inclined to better understanding the needs and analysing the situation, solving the problems creatively. All we need is to learn how to do the same using data and information presented. The demand for such roles is very high at the moment, be it any industry. If we can leverage the business knowledge combined with some tech skills, that the best outcome for both the individual and the business.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

AI and Machine learning is the future. Now that we are sitting on the wealth of information , using data Ethically and maintaining the security/privacy of data are going to be the most important aspects in near future.

In a normal day, what kinds of data / analytics activities are you involved in?

Lots of meetings, understanding business strategy, goals and priorities so I can make sure we're working on aligned initiatives. And meeting with my team to understand where things are at so I can update stakeholders, help remove roadblocks or obstacles, and prioritise if there is competing demand. Then inbetween I'm spending time on the Data Strategy, Data Governance initiatives and building the brand of the Data & Analytics team by sharing our successes with the business.

What are the biggest challenges you face?

Supply and demand problems exist in every organisation when it comes to Data & Analytics. The biggest gift I can give my team is ruthless prioritisation and being a gatekeeper to distractions from our key priorities. And then building the plane while flying it - that is, the need to build new data products while maintaining existing operations.

What would be the proudest or most enjoyable moment in your analytics career?

I really enjoy building new teams and seeing them come together and do great things. When I see my team happy and proud of their work and being valued and appreciated by their business stakeholders, nothing beats that.

What advice would you give to a woman wanting to get into the analytics industry?

Data & Analytics roles are a mixed of three skills - Computing, Statistics and Soft skills/business acumen. You don't need to be an expert in all three categories to be successful in an Analytics role. If you have an interest in using data to solve important business problems then reach out to your resident Analytics Lead, an industry leader, or myself(!) and start a conversation about what you enjoy doing and what roles might be aligned to your skills and interests. We need more women in analytics and progress over the past decade has been too slow.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

Certainly the evolution of privacy laws will play a role in how we apply and manage analytics. There are strong focuses in Health and Sustainability that will be gamechangers. And Cyber Security is right at the top of the agenda with the recent publicity of data breaches. I find the evolution of the workforce interesting and how we continue to deliver in tough economic times, with a hot talent market and ever-increasing business demand and expectations.

In a normal day, what kinds of data / analytics activities are you involved in?

Provide direction for my team, oversee their work and ensure its accuracy. Also, work closely with leaders across product and finance to support and implement high-quality, data-driven decisions.

What are the biggest challenges you face?

To enable the business to be more self-serve in data analysis 

What would be the proudest or most enjoyable moment in your analytics career?

Success of my team

What advice would you give to a woman wanting to get into the analytics industry?

Be humble, not afraid of change and keen to learn 

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

It will shift heavily to machine learning. Having said that, I still think the basics like descriptive, exploratory and diagnostics analyses cannot be ignored

In a normal day, what kinds of data / analytics activities are you involved in?

A good mix of time 'in the data' with various tools, as well as lot's of stakeholder collaboration. Top of mind throughout, is ensuring the right questions are being asked of the data, with the right benchmarks and that the resulting 'story' is synthesised to be clear, concise & visual.

What are the biggest challenges you face?

I love the balance of technical and softer skills in my day - always have. The challenge is having the time and head space to ensure we're constantly helping pave the way for better data literacy, democracy and governance across the business.

What would be the proudest or most enjoyable moment in your analytics career?

Many moons ago when I was on agency side, I faced a frosty reception from a CEO on value (or cost) of their loyalty program, vs their preference to spend on above the line media. As always, the data did the talking and I was able to show not only how valuable these loyal customers were, but how we could better understand them and even communicate  with them in a more relevant way, because of the program. They subsequently caught the 'bug' and invested heavily in their data, program and customers.

What advice would you give to a woman wanting to get into the analytics industry?

The biggest antidote to lack of confidence is knowledge, which in turn comes from curiosity. If I know my stuff I can always talk & engage confidently. So be curious. Ask a lot of questions, and embrace questions back (as that's a way to ensure stakeholders are confident and have understood you well also). In turn, the data will enable your stakeholders to make better, more confident decisions & discussions too. And always remember you're in the room because you're the expert, the one closest to that subject.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

Data literacy. I think technologically there's been amazing advancements in the last decade handling the 3 V's of data as well as accessibility of BI, visualisation and ML. Whilst the data doesn't lie, it is definitely easy to go down rabbit holes and wrong turns and it can definitely mislead if you're looking at (or for) the wrong thing. So as the proportion of people accessing & using data continue to scale, the skill set needs to scale with it.

In a normal day, what kinds of data / analytics activities are you involved in?

Product analytics to improve the product experience for the users. 

Work closely with delivery and business teams and responsible for generating data driven insights and identifying business opportunities.

Development of Dashboards for data storytelling and for data Visualizations.

What are the biggest challenges you face?

Measuring qualitative KPI metrics

What would be the proudest or most enjoyable moment in your analytics career?

Winning Bravo Award for contribution made in improving net promoter score

What advice would you give to a woman wanting to get into the analytics industry?

If you made up your mind that you can do this, you have already taken a head start. Once you start the journey there's enough and more resources available. Grab all the opportunities, do research and stay committed and true to yourself. your commitments, abilities and skills will be paid off with a rewarding career.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

real time data analytics with real time data refresh and availability of data for everyone to consume

In a normal day, what kinds of data / analytics activities are you involved in?

Data extraction, exploration and analysis, visualization

What are the biggest challenges you face?

Outdated and inconsistent data in database create challenges in drawing actionable insights

What would be the proudest or most enjoyable moment in your analytics career?

Ability to create story from data and insights that are easy to understand for stakeholders

What advice would you give to a woman wanting to get into the analytics industry?

Continuous learning and awareness about current market scenario and technology

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

Ability of machines/AI to take over human effort in doing things

In a normal day, what kinds of data / analytics activities are you involved in?

In a normal day, I'm usually involved in customer solutions, data pipeline, and generating insights. I'm also responsible for highlighting focus areas for the team. For example, if we're working on a project for a specific customer, I'll review their data and analytics needs to determine how best to approach the problem. This might involve building a custom data pipeline or report, or it might simply be providing them with some insights based on our existing data. In either case, my goal is to help our team deliver value to our customers.

What are the biggest challenges you face?

One of the biggest challenges is that some people are not open to change. They resist change to existing processes and do not fully trust the results of analytics. This can make it difficult to get everyone on board with new initiatives. Another challenge is that depending on manual inputs can be time consuming and prone to error. This makes it difficult to get accurate data in a timely manner.

What would be the proudest or most enjoyable moment in your analytics career?

For me, it is when I am able to make a real impact on the strategy of a company or aid in changing an existing process to reach that goal. It is gratifying to know that my work is having a real and positive change on the business. These moments reflect the value that analytics brings to organizations and help solidify my role as a strategic partner within the company.

What advice would you give to a woman wanting to get into the analytics industry?

If you're a woman who's interested in getting into the analytics industry, my advice is to go for it! You're already analytical by nature, and extending that into your professional life will only make you more successful. Curiosity is key in this field - keep asking questions and looking at the world through a data lens. You'll be amazed at what you can discover. And finally, don't forget that you're part of a wonderful community - there are lots of people out there who are willing to help you on your journey.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

AI and predictive analytics will continue to revolutionize the field of analytics. By providing real-time insights, AI will help businesses make more informed decisions and enable them to operate more efficiently. In addition, predictive analytics will become increasingly important as we strive to anticipate future trends and understand how they will impact our lives and work.

In a normal day, what kinds of data / analytics activities are you involved in?

One of the beautiful things about my role is the sheer variety of projects I get to work on that use data and analytics in a positive way to inform decisions and make valuable and impactful change in the world around us. Working for an analytics vendor like SAS, as the analytics landscape adapts, my role does too.

Some of the activities I frequently find myself doing now are supporting government agencies to uplift their analytics efforts to improve citizens’ experiences and outcomes, analysing data myself to develop meaningful technology demonstrations or deliver on specific projects, and mentoring and guiding the next generation of STEM leaders. 

I’m currently working on a project to improve early interventions for children at risk using statistics, geospatial analysis, machine learning and natural language processing. The project team is all women from around the globe, with altruism and kindness at its core.

What are the biggest challenges you face?

My biggest challenge is working across siloes – data, technology and people siloes. Connecting a team of people to act and break these down in an appropriate and positively impactful manner is tricky, particularly when politics and power are thrown in the mix. I also often find people who are pro-change, for everyone but their team, which again is a tricky thing to manage. 

Working in government, I also encounter a lot of sensitive topics, which while being involved in the teams trying to improve the outcomes is great, sometimes can take a toll on you at a personal level. Having a fantastic support group has been vital to my success in these areas.

What would be the proudest or most enjoyable moment in your analytics career?

I’ve worked on some amazing and groundbreaking projects including helping medical professionals triage at-risk sepsis patients, assisting child safety workers to identify early warning signs of child abuse and neglect in case notes, and using a deep learning algorithm to screen for breast cancer in tissue sample images. Having a positive impact on the community is so fulfilling! 

I have also had my work recognized by the Australian Reseller Network (ARN) at the Women in ICT Awards (WIICTA) 2022, as the Rising Star in the vendor category.

What advice would you give to a woman wanting to get into the analytics industry?

It might sound cliché, but you have to truly believe in yourself. Picture yourself in the role you want to be in, on the project you want to work on, with the recognition you want. Speak about the great work you are doing as if you’ve already done it and achieved it. If you show others you value your own diversity, experiences and unique perspective, they’ll follow suit and help you achieve your goals. 

Also, don’t be afraid to stand out a little in what you do. Be authentically you, be open about your goals, and be “unignorable”. Whether that’s talking yourself up, or simply wearing the pink suit, the rest will fall into place.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

I’m most interested in how we as a community maintain ethical practices in health data and analytics.

While maintaining the privacy of health data is clearly of importance due to misuse of information – think biosecurity keys and insurance premiums for having genetic markers - I can also see huge benefit to a more holistic view of health and wellbeing with relationships between bodily systems becoming clearer as research evolves. 

The discussion then becomes how much data is shared and with who. Thinking from a broader point of view, who owns that data? Is it the individual who may not necessarily be analytically literate to interpret their own data, let alone keep it secure? Is it the provider of treatment – how is that managed for multidisciplinary conditions, or across a consolidated national health system? Or health insurers who may hike the costs for those unknowingly predisposed for adverse conditions? 

It's certainly going to be a challenge and a delicate balance however the space evolves. 

In a normal day, what kinds of data / analytics activities are you involved in?

Frisk is an Adelaide-based data intelligence company. We deliver next-gen data augmentation and decision optimisation solutions, to private and public sector clients. Our aim is to give clients the power of sight, across both structured and unstructured data, so that they can derive meaningful insights and make optimal business decisions. My day-to-day involves collaborating closely with stakeholders to understand their ever-changing business needs and how Frisk can assist them in achieving their objectives. From here, we develop solutions, applying a wide range of technologies including, data ingestion and indexing, artificial intelligence specifically machine learning, natural language processing and graph/network analytics.

What are the biggest challenges you face?

In my current role, the biggest challenge is demystifying AI, particularly for small & medium enterprise who are keen to start adopting the technology and realising the benefits but are unsure where to start. That along with balancing innovation and risk; ensuring new rapidly advancing tech meets security and data governance requirements.

What would be the proudest or most enjoyable moment in your analytics career?

I don’t have one most enjoyable moment in my career, but a highlight has been the people I have met and worked with along the way. Forming a team of talented people, with diverse experience and skills, to deliver a project successfully, is always a thrill. Seeing stakeholders get excited about the solution and how much value it will bring, drives me to start the next project! Coaching and mentoring new talent, is also a highlight; providing support and guidance for people to fast track their career into roles where they love what they do, every day.

What advice would you give to a woman wanting to get into the analytics industry?

Every day is a learning curve, don’t wait to be a master. One thing I love about the analytics industry is the variety – the problems to solve are rarely the same, and the technology is constantly evolving. This can be daunting for people considering a career in analytics, but acknowledging and embracing these things, can bring valuable career opportunities and experiences.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

Many large enterprises have already introduced and are realising the benefits of graph analytics. This trend will continue to grow, however an increasing number of small & medium enterprises will start adopting the technology, as it becomes increasingly accessible. As graph analytics is further embraced, I am excited to see how the public sector in particular, applies the technology in order to deliver improved outcomes for Australian citizens.

In a normal day, what kinds of data / analytics activities are you involved in?

Frisk is an Adelaide-based, NextGen agile data intelligence company and technology platform that provides artificial intelligence, data augmentation and decision optimisation solutions to SME, enterprise and government customers. 

The Frisk product is designed to revolutionise the way organisations utilise and augment data to deliver powerful insights that optimise decision-making, delivering tangible commercial benefits to the business. 

Some use cases include -  

- Enterprise search 

- Fast-tracking FOIs 

- Pinpointing PII 

- Legal Discovery  

For the last few years (in different capacities) I have been managing the marketing and communications for the brand. This also includes providing insight, trends and recommendations for product development.

What are the biggest challenges you face?

It is still a male dominated industry, although in my experience women are wholly embraced. 

One of the biggest challenges is still to get industry and businesses to recognise the importance of a sophisticated and sustained data strategy, and the insight that is hidden within data.  

Another is around the understanding of, and showing the importance of unstructured data. By 2025 it is estimated that over 80% of all data will be unstructured, yet many businesses are not prioritising or properly indexing this type of data. 

Hopefully over time there is more awareness of the value of data and the insights it can uncover.

What would be the proudest or most enjoyable moment in your analytics career?

I was part of the team that prepared the brand, strategy and plans for a capital raise. That was a high point. 

What advice would you give to a woman wanting to get into the analytics industry?

Keep on fighting the good fight!

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

The application of AI, the security of data (also linked to AI applications like Chat GPT), the democratisation of data (making it easier for end-users to get insights) and unstructured data. 

In a normal day, what kinds of data / analytics activities are you involved in?

I explain to potential customers how to use SAS Analytics' solutions to improve their business outcomes.

What are the biggest challenges you face?

The biggest challenge is to find a way to explain in simple words something that can be very complex, such as Machine Learning. 

What would be the proudest or most enjoyable moment in your analytics career?

When I find a good story that explains well what the data analysis is telling me. And when I explain the results in an easy way that everyone can understand.

What advice would you give to a woman wanting to get into the analytics industry?

I'd tell her to make sure she learns a very effective way to communicate her findings and convey the message to business leaders and managers. Also, I'd tell her to learn very well the foundation of statistics/Math and to be up to date with the latest trends in the market. Finally, I'd also encourage her to learn about some business subjects as this will help her with the interpretation of the results. 

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

The ethical use of Analytics. How to make sure any company is using analytics in an ethical way.

In a normal day, what kinds of data / analytics activities are you involved in?

I am lucky enough to spend my days with many analytics professionals and business stakeholders to discuss how we can collaborate to deliver the benefits of data and analytics to organisations.  I work on developing analytics solutions and products that will assist business teams to deliver benefits to their end customer.  I also focus on ensuring we have a sustainable and relevant data and analytics strategy to support the organisation's objectives.  With the rapid pace of change, the analytics team need to be aligned to business outcomes and continually refining how the engage with the business and deliver those outcomes and benefits.

What are the biggest challenges you face?

One of the biggest challenges is change management.  All data and analytics products should drive some level of change to support the stronger use of data and analytics.  To truly deliver value from analytics products, the organisation needs to work differently and that involves change management activities to consume the solution and ensure business stakeholders trust and act on the data and/or solution.

What would be the proudest or most enjoyable moment in your analytics career?

I feel most proud when I see younger analytics professionals see the impact they have made on an organisation with their work.  Coaching and mentoring people is something that gives me joy and hopefully gives younger professionals a way to fast track their craft and achieve their personal goals.

What advice would you give to a woman wanting to get into the analytics industry?

My advice would be to focus on your business knowledge as well as your technical skills.  I recommend that you collaborate closely with your stakeholders to ensure your work is actionable and delivers value every time.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

I see a focus around data literacy with a lot of value coming from how we better collaborate across the many diverse teams that need to come together to deliver a successful analytics and AI project.  Success is a team effort and very relevant to data science as we move into the age of AI and advanced uses of data.

In a normal day, what kinds of data / analytics activities are you involved in?

I am involved in anything to do with marketing data! This includes creating target audience lists for email campaigns, creating and analyzing reports for pre and post marketing campaigns, developing strategies for nurturing contacts via automated campaigns, ensuring our systems are working with each other and have a good data quality and using output from analytical models for analysis.

What are the biggest challenges you face?

One of the biggest challenges I face includes trying to integrate different systems and sources of data whilst ensuring data accuracy. Another challenge is around data privacy issues and ensuring cultural differences are addressed when running global campaigns.

What would be the proudest or most enjoyable moment in your analytics career?

My proudest moment is when data analysis supports the hypothesis we have made about a particular business problem.

What advice would you give to a woman wanting to get into the analytics industry?

The advice I would give to all women is to be curious about numbers and data and understand how it flows through the tools. This will give you a greater understanding of the tools and assist you in making better and more informed decisions. Also, be loud and assertive when it comes to something you believe in and have to present your findings to your peers. Don’t let anyone tell you that you can’t make it in this industry!

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

One of the most interesting aspects is the constantly evolving AI platforms available in the markets. Companies need to keep on top of all these various platforms and when the time is right, leverage it to their advantage while ensuring ethical standards are met and the platforms are safe and secure.

In a normal day, what kinds of data / analytics activities are you involved in?

Every day is different but its mainly around working with teams/businesses/clients on 

1. Understanding their business objectives and challenges. And how can they effectively meet their business goals. 

2. Helping them realise the value of data and actionable insights. How can they use the data & integrate different systems to act on that data.

What are the biggest challenges you face?

Democratisation of data and ensuring we have a proper governance framework around it

What would be the proudest or most enjoyable moment in your analytics career?

Some of the proudest moments have been the ones where I got to witness teams fundamentally change and start using data to make any business decisions.

What advice would you give to a woman wanting to get into the analytics industry?

Data and analytics can sometimes be a broad term and can cover off different areas. Try out those areas, teams, see what clicks and what you enjoy the most. 

In terms of technical skills, SQL would be a good starting point; more so to understand logic & the coding world. 

More over, Data and Analytics is a fun world of story telling & opportunities. You will always find something interesting to do & learn.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

With this enormous amount of data available, it'll be interesting to see how can we simplify these signals and convert data into insights and action easily.

And of course, with innovation, how do we balance it with privacy & ethics.

In a normal day, what kinds of data / analytics activities are you involved in?

->AI

->Data integrations between Engineering Assets and IT Systems (OT/IT convergence, IIoT, I4.0 and PLC/Scada Control Systems Automation)

->Complex System of Systems Architecture

What are the biggest challenges you face?

Enabling data linking and aggregation to and from central stores/data lakes across OT engineering asset and IT corporate systems networks to enable near/real time data driven decision making and predictions in real time. Security policies often inhibit this.

What would be the proudest or most enjoyable moment in your analytics career?

Several!

1. Completing the Data Architecture Strategy and designing and implementing a Kafka real time data platform to enable ship to shore communications, triggering asset and strategic decision making for defence

2. Recent AI for engineering assets academic paper published

3. Having implemented AI/ML/data integrations for data driven decision making, optimising and automating processes for several organisations in Health, defence and  mining including autonomous vehicles and scheduling

What advice would you give to a woman wanting to get into the analytics industry?

Come and join the Systems Engineers on the engineering asset side - model based systems, automation and virtual twining - there's not many of us!

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

Overcoming cyber security policies to enable data linking and mining between OT and IT networks in real time.

The number of types of analytics/machine learning streams is now large - seeing where the consolidation will be - chat bots versus automation (such as cars) trade off driving that consolidation

In a normal day, what kinds of data / analytics activities are you involved in?

Being a start up, the activities vary which I like. Our main focus is building an AI tool to help organisations drive cultural change to improve employee experience and performance. I help with development, review, design, and project management. We also do data analytics consulting, where I help scope, deliver, review, and manage stakeholders across different projects. I am also helping train up more junior team members.

What are the biggest challenges you face?

Over the years I’ve definitely had to face the feeling of imposter syndrome. All through my life, from my STEM electives in high school, to uni, to the workplace, I’ve definitely noticed the lack of females around me. I was also not confident in my abilities, and genuinely felt out of place and like a fraud a lot of the time. Over the last few years though, with the support of amazing managers, colleagues, and mentors, I’ve realised that I am great at what I do, and that I do deserve to be where I am. I do still have moments of doubt, but I’m finding it easier to push them aside now.

What would be the proudest or most enjoyable moment in your analytics career?

There have been many great moments. I think my proudest would be when I scored very highly in my performance review at my previous company where there were a lot of very smart and talented people. For me, this helped squash any thoughts I had that I wasn’t good enough, and also helped validate that the years of hard work to get where I had had paid off.

What advice would you give to a woman wanting to get into the analytics industry?

Do it. It’s a fantastic industry to be a part of. I absolutely love my job and the people I get to work with. Also try to find a mentor, preferably female, in the industry too to help give advice and ask questions of. I find this is a great way to broaden my network and learn different perspectives too.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

Personally I think watching data become more widespread and used to its full potential will be incredible. It’s still amazing how many organisations are not doing this yet, and it’s fantastic seeing how impressed they are with something we consider to be quite basic.

In a normal day, what kinds of data / analytics activities are you involved in?

In a normal day I would be involved in a myriad of data analytics activities this includes data extraction and processing, creating data workflows, data migration, data querying using SQL and other tools, designing, creating and implementing dashboards through tableau and google data studio, building forecast models, providing insights and analysis to wider stakeholders as well as really using data to accentuate what the highlights/hotspots are and tell a story with it.

What are the biggest challenges you face?

One of the biggest challenges I face, is to really hone in one focus area and provide some sort of actionable insight regarding it. This is because there is usually a plethora of contributing factors so it can be slightly difficult to drill-down into one or two areas where stakeholder can quickly and feasibly action it. Also, balancing day-to-day requests with projects and data innovation initiatives which may ultimately hugely assist the business, so working with priorities can also be another challenge.

What would be the proudest or most enjoyable moment in your analytics career?

There are many proud and enjoyable moments within my analytics career but I would say one highlight would definitely be creating and implementing a Leads Performance Dashboard which really changes the way our stakeholders look at and understand data on the leads funnel perspective. Providing them with a lens that they never had visibility on is really rewarding. To see my stakeholders actively using it to guide their conversations and ultimately self-serve to improve their overall business health and lead generation. This involved a lot of work around the data design and workflow modelling, in order to join several datasets with the accurate logic and business rules. As well as the overall dashboard design and creation so that the data and information can really be understood and well received by the users. Additionally, I used an iterative approach so that stakeholder feedback is used to constantly improve the dashboard and ensure it is widely well received.

What advice would you give to a woman wanting to get into the analytics industry?

To just go for it, it is such a large industry and the best bit about it is you will always be learning and experimenting with new technologies. I would say one key piece of advice is to still have that technical skills, but then also really place importance on your stakeholder confidence, communication and presenting skills as this is what really allows your data analysis to come to life and differentiates you from others in the industry.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

For the future of analytics I would have to say AI and machine learning will certainly be the most interesting and groundbreaking aspects. This is as there is so much we as an industry can apply this to and as we familiarise ourself with it more in our day-to-day activities it can be really powerful and change the way we employ our data.

In a normal day, what kinds of data / analytics activities are you involved in?

My current role is about helping various organisations drive and implement their analytics/DS strategies through the use of technology. I am involved in conversations around how  to get started in this journey and how to scale it out to gain the business value you need to justify the investment.

What are the biggest challenges you face?

Getting a seat in the table where critical decisions are made. It’s very rare to find a peer or a female leader in the industry I work in. It’s changing slowly and I’m grateful for all the women before me who stuck it out and built a career and paved for me and others to be put on stage and be heard

What would be the proudest or most enjoyable moment in your analytics career?

Travelling the world and meeting people from all over the world who has the same passion and interest. My analytics career has allowed me to move to Australia and build a life here

What advice would you give to a woman wanting to get into the analytics industry?

Back yourself and remain resilient. You can have a career as well as a family life - don’t quit even before you got started

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

I’m looking forward to seeing analytics being widely used  by non-data people. I’m also looking forward to more women leaders to analytics roles in major corporations in ANZ

In a normal day, what kinds of data / analytics activities are you involved in?

Utilisation of R to carry out analytics projects that support marketing and strategy, as well as campaign targeting guidance. Also have a focus on operational risk minimisation such as the automation of outlier detection processes

What are the biggest challenges you face?

Ensuring integrity of data insights, and 'reproducability' of outputs, in an environment where changes to data sources can occur frequently.

What would be the proudest or most enjoyable moment in your analytics career?

What advice would you give to a woman wanting to get into the analytics industry?

Make sure you retain a focus on the practical outcomes of your work, not just the nitty-gritty detail of the data. It's often ok for analysis findings to be 'directional', not necessarily perfect.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

Hopefully finding better/easier ways to quantify the benefit of analytics projects, which would help with prioritisation.

In a normal day, what kinds of data / analytics activities are you involved in?

primarily as a consultant working with customers to achieve their goals - whether it's wrangling data, building a Machine Learning project, or deploying and automating data/ML workflows. I also lead the Dataiku teams within Aus/NZ and Japan/Korea.

What are the biggest challenges you face?

A few of our customers have difficulties in prioritising activities / projects with us - which may be as a result of internal politics, or high valued use cases not being immediately obvious. In instances like these - our partnership with our customers is extremely crucial, to help shape and influence their strategy. Another big challenge I commonly face is working across different countries - I currently lead the Data Science teams for Australia, New Zealand, Japan & Korea. My colleagues in Japan & Korea are great to work with - that said, we have to respect each country's culture (the way they think, and operate). These countries are typically very conservative, and follow certain protocols when it comes to doing business. In instances like these - I heavily rely on my Japanese & Korean team mates, in ensuring I am across and conscious of how to work with these customers (along with their continuous support and endorsement).

What would be the proudest or most enjoyable moment in your analytics career?

Working at Dataiku - which has exposed me to different cultures workwise.

What advice would you give to a woman wanting to get into the analytics industry?

Look out for data analyst type roles, that will help shape up some basic analytical skills. Look to also upskill yourself so that you can demonstrate your ability to learn on the job (putting together either an Excel analysis, or a Python project). Getting endorsement, or support from colleagues, someone in the industry also will significantly boost your chances of tapping into the industry

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

With the rise of low-code tools and platforms (like Dataiku) - this is gradually reducing the barrier to entry: allowing subject matter experts to focus on what they know best, but being able to analyse their data in a systematic and scientific manner.

In a normal day, what kinds of data / analytics activities are you involved in?

As an expert in advanced AI modelling with a focus on detecting defects in pipeline inspection, my daily activities involve a wide range of tasks. I engage in advanced analytics activities such as data cleaning, transformation, and normalization to ensure that the data is accurate and consistent. I create algorithms and cutting-edge AI models to detect defects in pipeline inspection, using techniques such as computer vision,machine learning and deep learning.I also constantly engage in gathering and processing data, creating advanced AI models, and managing data assets. Also work closely with other team members to ensure that the data assets are properly integrated into the project and are easily accessible for analysis and reporting.I play an instrumental role in improving the accuracy and efficiency of the VAPAR AI system

What are the biggest challenges you face?

There are many challenges that I may face in my analytical career as an AI modelling expert focused on detecting defects in pipeline inspection. These challenges may include keeping up with rapid technological change, managing large volumes of data, ensuring the accuracy and fairness of my models, and communicating the significance of my work to stakeholders. To overcome these challenges, I need to develop new skills and strategies, collaborate with domain experts, and invest in effective communication strategies. By doing so, I can ensure that my work remains impactful, accurate, and valued in the field of pipeline inspection.

What would be the proudest or most enjoyable moment in your analytics career?

One of the proudest moments of my data science career was when I built a model from scratch and taught it to detect objects in images using computer vision techniques. It was a challenging project that required a deep understanding of the underlying algorithms and a lot of trial and error. There is something incredibly satisfying about watching a model learn and improve over time, almost like watching a child grow and develop. The more I worked on the project, the more I became passionate about computer vision and the possibilities it offers for solving complex problems in a wide range of fields. One of the most exciting aspects of building this model was the opportunity to understand and imitate the visual abilities of humans. By analyzing large amounts of image data and using advanced machine learning algorithms, I was able to create a model that could detect objects in images with a high degree of accuracy. The project was also impactful because it had the potential to be used in a variety of applications, from surveillance to medical imaging. Knowing that my work could contribute to improving people's lives was incredibly motivating and made me even more committed to pushing the boundaries of what is possible in computer vision. Overall, building this model from scratch and watching it develop over time was one of the most rewarding experiences of my career. It reminded me of why I became passionate about data science and anlytics in the first place and motivated me to continue working on projects that have the potential to make a difference in the world.

What advice would you give to a woman wanting to get into the analytics industry?

My advice to any woman wanting to get into the analytics industry is to jump right in and give it a go. Although it may look difficult and hard to get into at first, a small effort can go a long way in making it work. To start, I recommend gaining knowledge and experience in data analysis, machine learning, and programming through online courses and certifications. It is important to stay updated with the latest trends and technologies in the field by attending conferences and networking with other professionals. Finding a supportive community of peers and mentors who can offer guidance and advice is also critical. Look for organizations and initiatives that support women in analytics to build your network. It's important to keep in mind that the analytics industry is constantly changing, and it's important to be flexible and adaptable. Embrace new technologies and approaches, take risks and try new things. Lastly, don't let any perceived barriers or obstacles hold you back. With the right mindset, perseverance, and passion, you can achieve great success in the analytics industry.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

In terms of the future of analytics, the most interesting aspect is the potential impact of generative and assistive AI. These technologies have the potential to revolutionize the way we approach data analysis, making it more accessible and inclusive to people from diverse backgrounds. Generative AI can help automate the process of creating new data, which can be especially useful in industries such as healthcare, where there is a shortage of real-world data for training models. This can lead to more accurate and efficient diagnoses, treatments and ultimately, better patient outcomes. Assistive AI, on the other hand, can help people with disabilities to overcome barriers to access and participate in analytics. By providing real-time feedback and assistance, assistive AI can help individuals with visual or hearing impairments to participate in data analysis and gain valuable insights. Another interesting aspect of the future of analytics is the increasing importance of data ethics and privacy. As the amount of data being generated continues to grow, it is important to ensure that the use of this data is ethical and respects individuals' privacy rights. Overall, the future of analytics is exciting, with the potential to make data analysis more inclusive and accessible, while also improving accuracy and efficiency. As we continue to explore the possibilities of generative and assistive AI, we must also be mindful of ethical considerations and strive to create a more transparent and responsible data-driven world.

In a normal day, what kinds of data / analytics activities are you involved in?

I have the privilege to lead the solutions for Risk Modelling & Decisioning at SAS. We use data and advanced analytics to better quantify risk, such as credit risk, liquidity, and climate risk. Advanced risk analytics enable our customers to make better risk-based decisions. We utilise a wide range of data types, including structured, unstructured and geolocated data, together with a wide range of algorithms including statistics, operations research and machine learning to quantify risk for everyday lending decisions or extreme events such as climate risk shocks.

What are the biggest challenges you face?

We are currently employing Artificial Intelligence and Machine Learning (AI/ML) to automate typical risk management tasks such as the ongoing validation and monitoring of models. We are also looking at the responsible application of AI/ML for highly regulated models. Some of our biggest challenges are to make the AI/ML models more explainable and how to address any biases that may arise.

What would be the proudest or most enjoyable moment in your analytics career?

I’ve had the privilege to write a paper for the World Bank on the responsible use of AI/ML for Credit Scoring and its impact in developing countries. Recently, I've published a book entitled: Risk Modeling: Practical Applications of Artificial Intelligence, Machine Learning, and Deep Learning.

In my job, I have the opportunity to interview a range of industry experts on the practical applications of AI/ML in banking and advise organisations and regulators on the safe and responsible use of AI/ML. AI/ML is a rapidly evolving field and becoming an intricate part of the fabric of our society and how we engage with services providers, not only in banking.

And lastly, under my leadership, the SAS product for Risk Modeling modernised to our new platform, SAS Viya, and received international recognition as best consumer credit modeling software in 2020, 2021 and 2022.

What advice would you give to a woman wanting to get into the analytics industry?

Speak up. The industry desperately needs your expertise, your experience, and your perspective. Talk about diversity and demand it from your teams. Diverse teams are better equipped to identify and remediate biases in the workplace.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

AI/ML are developing at groundbreaking speed. For example, we see impressive and exciting innovation in natural language models. These technologies have transformational potential in rapidly automating freeform text generation and summarization. The next step following automation will likely be the optimisation of processes.

In a normal day, what kinds of data / analytics activities are you involved in?

Manage Data Analytics Projects across different sites for our client. It's always beneficial to have worked in the weeds before managing the team as it helps you contribute to the decision making, provide suggestions based on experience and expertise and directly contribute to the success.

What are the biggest challenges you face?

Data is always an interesting domain to work with. There are times you tend to go with your intuition but the inference you get from the data might be completely different. Patience and attention to details are the key when you work with data. Too many tools in the market and I always try to upskill but being upgraded always is a challenge. Having worked in Consulting environments has taught me to spin around different domains at the same time and exhibit greater potential in all of them.

What would be the proudest or most enjoyable moment in your analytics career?

My first proudest moment would be identifying the future of Analytics in very early days and making my switch. I have always loved numbers since childhood. Not sure how I ended up in Engineering and not Accounting. Playing with data and numbers again in this domain makes me love my job each day. Being in Data Analytics industry lets you contribute to both worlds of tech and Management which is what I thoroughly enjoy. Working across various domains and always being able to provide valuable insights and infer decisions from the data makes you feel very included. When the organization makes a decision based on your Data Analysis and Modelling and implement a change and when the change is measured weeks/months after and the results provide wins to the organization is always my proudest moment. And am so glad am able to make those moments more often :)

What advice would you give to a woman wanting to get into the analytics industry?

There is a difference between Data Analysis and Data Analytics which most people tend to miss. But these differences in the Data Analytics domain leverage various paths for woman. There are multiple roles with from being an Analyst to a Programmer to being in Visual Data Management to a front-End developer to a back-end data management person to a Data modeler to Data Governance to an Architect and few different roles. These various options let you fit in different buckets based on your interest. The only key would be 'Never be afraid to pick any role'. As long as you are open to learning, nothing is difficult. If you have had a career break, or you want to start fresh, come in energized and am sure you can interleave into the data industry very quickly. 'Data' is everywhere and is the main essence of all the modern technology. So, you will always have a spot here. I feel woman have extra skill in working through data, identifying anomalies and coming up with insights from all points of view. This additional skill will always let you outshine from the crowd. Honestly, all of us work with data each day at home in various ways from analyzing the food pattern for our kids, likes and dislikes of people around us, analyzing the spend for our household, predicting the future spend based on current trend for the month/year and Analytics is all about working on a bigger data set to provide similar insights :)

Irrespective, as long as your passionate, have the will power and stand up for yourself, we can always win the world!

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

We hear of many terminologies each day - Artificial intelligence, Predictive analytics, Augmented Analytics, Hyper personalization etc. New innovations always come with new challenges. Something new at most times will be better than the previous one. Way forward would be interesting to see how we beat through these challenges on the journey to maturity. As we get through new technologies Data Governance would be the key and proactive Data Stewardship may be at high demand. 

Robotics Automation as much as is advantageous, people also seem to look at it as a threat. In the future we may be working towards a lot more Automation. We can expect regulations to grow tighter in the coming years. Companies must toe the line between ensuring information privacy and accessibility while staying agile and competitive.

The trend line has always been growing and the prediction into the future for Analytics is always relative as well.

In a normal day, what kinds of data / analytics activities are you involved in?

I lead a dual team, 2 people in the Data Governance and Data Management function, and 20+ people in a Data Engineering Function. I help flesh out strategy, plans and solutions for our Enterprise Data Platform. I also have designed and commenced rolling out a new Data Governance Framework and Data Ownership approach. I specialise in design of solutions that deliver a customer 360 view, MDM and Reference Data Management.

What are the biggest challenges you face?

Data lifecycle on-boarding combined with Data Literacy gaps is the biggest daily challenge. A secondary challenge is the knowledge uplift that is required in terms of data ownership and how that translates to immediate business benefits like data protection, data value and fit for purpose metrics. A third challenge is building consistent, high performing teams that display ownership of their outcomes and process; in an industry that is in high demand and we have high churn due to better, shinier offers; people skilled in delivering parts of the data lifecycle may at times join us with ways of working and approaches that need to be refined/improved.

What would be the proudest or most enjoyable moment in your analytics career?

Landing in the current role is probably my proudest moment, being able to merge Data Management with Data Engineering, through process, education, knowledge of what is the right approach and sheer grit.

What advice would you give to a woman wanting to get into the analytics industry?

I have 4 daughters, ranging 5 to 18. I encourage them daily to look at life around them, data is everywhere when you stop and think about it. Analysis is at its core the summation of an aggregation of data. My advice is start on the basics and core principles, not to chase shiny software and tools. You can do analysis with pen and paper. Google the Rose Chart, created by Florence Nightingale. She did not have Tableau, or PowerBI or Lavastrom or Alteryx or what ever the newest myriad of options in the market.

So start by looking at the data around you, in your life (personal finances) or work (invoices) and use that data to answer some questions.

I often meet data practitioners who skipped the theory and got straight to the tools and they struggle to deliver context. To be good at analytics you are foremost a problem solver; and all good problems solvers do these 3 things: -Define the question being asked (what do business need to know from data)

• Write up the decision the answer will give (KPI)
• What is the action business will undertake when the answer is given? (Outcome)

When you simplify the work like this, you can do analysis using any tool. The other advice I would give is speak to anyone already in analytics or data and ask them to show you what they do in their daily work. It's a great way to get a view of which of your current skills are transferrable.

And lastly it's never too late; I only started using a computer at 21, before that I was a visual artist.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

I think for humans the most interesting is the personalisation aspect; both good and bad outcomes - refer Minority Report. For data leaders it's important we work very hard to mitigate the negative aspects often denoted in sci-fi.

AI and ML is all the craze right now, as was BI 15 years ago or big data etc. I don't believe we have matured enough in how we collect, store and manage data, to derive useful data outcomes for humanity; and hence we have infant chat agents who propose to be philosophers.

I also would love to hope that we get better at data solutions to use this for medical achievements and some work is being done in this field right now that excites me, where we are decoding the human gene much faster than we had before.

In a normal day, what kinds of data / analytics activities are you involved in?

a. Requirement discussions with stakeholders/external teams to understand the Data requirements, business impacts and system impacts on our existing solutions.

b. Querying the Data Lake for Data Discovery and analysis purposes

c. Performing data analysis to figure out how business requirements/Acceptance Criteria will be fulfilled using data including

i. Investigating what datasets are required for analysis and from which source systems

ii. How the datasets will be linked to each other

iii. Which data fields are required to fulfil Acceptance Criteria

d. Creating Stories and Data Mapping sheets for developers to implement the solution.

What are the biggest challenges you face?

a. Huge organisations like mine where the same data is used by various teams sometimes houses unintended data silos. i.e. different teams trying to analyse the same data/ achieve the same data solution for different purposes. It’s hard to find teams with synergies and not re-invent the wheel. We are gradually progressing on breaking down these data silos but there is still a long way to go.

b. Knowledge Management is key to any organisation’s success and data is its biggest asset. And the biggest danger is when knowledge about data resides in an employee’s brain. That’s one challenge I have faced – finding data SMEs because not all knowledge is documented. Which is why I make it a point to document all the knowledge I have so it can be used by whoever needs it.

What would be the proudest or most enjoyable moment in your analytics career?

a. I came into the Analytics domain out of interest and not just because of my qualifications. Hence, 90% of what I have learned in this domain is through hands-on work. In my early days of Data Analytics career, I was given the task of producing a Power BI dashboard on the organisation’s quarterly resource management including both $$ and human resources. This dashboard was to be used to track the demand and allocation of resources across the company on a quarterly basis. I was involved in the end-to-end activities including data discovery, analysis, requirements gathering and Power BI build. At the end of it, I was able to produce this dashboard without any previous working knowledge of PBI, by learning as I went. When the organisation’s Planning committee started relying on the dashboard to track resource demand vs allocation, that moment was a massively rewarding for me as I witnessed my contribution to the business.

What advice would you give to a woman wanting to get into the analytics industry?

a. I would love to share the best advice I have ever got which applies more to women than to men. Don’t believe in the myth that working in STEM industry means working over-hours, working harder than you would at other kinds of jobs or having to step aside from commitments in your personal life that you wish to pursue. Same goes for promotions in these fields. All it involves is you learning to manage your time differently which comes with experience.

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

a. I feel strongly about simplification. Therefore, what excites me the most is new technologies like Data Lakes that help make different kinds and formats of data in the same location for everyone to use using a common platform. A great example is Data Bricks which is helping organisations enable this. If an organisation manages to connect all the systems that capture data to a common data management platform, this will simplify the process of accessing data for everyone and the possibilities this will open in terms of solving problems using data analytics are infinite. Many organisations have already started the journey to achieve this target state but there is still a long way to go and I am excited for that.

In a normal day, what kinds of data / analytics activities are you involved in?

It varies from looking at how different datasets, including network and usage data, can tell a story about customer experience and making recommendations on the next steps and investment decisions. Understanding different platforms and how to work with them best from an ad-hoc to streamlined perspectives. Also working with the business to identify key use cases and processes that can be improved using Machine Learning/ Artificial Intelligence tools and technology.

What are the biggest challenges you face?

Keeping up with the evolving data landscape can be challenging. Finding a balance between having deep domain understanding and speed to delivery means I need lean on others more at times.

What would be the proudest or most enjoyable moment in your analytics career?

Making direct impact to our customers including helping provide services to domestic violence survivors and those in remote communities/schools without internet access through lockdown as well as building an analytics tool that help prioritise business investments.

What advice would you give to a woman wanting to get into the analytics industry?

Get your basics down pat - SQL and Python. Practice visual storytelling with the data you have - know the questions you are trying to answer before diving into the details. Formulate hypothesis that you can test. Get into fun projects in your spare time (budgeting using your own data can be very helpful) or get across competitions like Kaggle and GovHack. Have fun with it!

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

More and more of it will be so automated and ingrained in our lives that we don't even think twice about it. Especially with the increasing use of generative AI, policy makers will have to keep up on making sure that regulations are in place with ethical use as it becomes common practice.

In a normal day, what kinds of data / analytics activities are you involved in?

I manage a large global team that delivers Executive, Financial and operational performance Reporting of key company metrics for Senior management and customers. We are trusted advisors for providing high quality reports/dashboards/insights that solve business problems and drives effective decision making.

What are the biggest challenges you face?

1. Executive Support to improve Data Literacy - The sponsors / execs may not have a deep understanding of the foundation and advancements in the Data Analytics field. They sponsor short term initiatives, which may not necessarily be sufficient for continuous focus on digitizing the organisation.

2. Data Curation - There is a huge amount of data available within the organisation and out there. Data curation is overlooked many a time, leading to each project weeding the data to their specific purpose. 

3. Legacy Data - As a company completes a decade (even lesser these days), there is a pile up of legacy systems, which need to interact or coexist with modern systems and data, leading to complexities in getting a complete view.

4. Data privacy - This is becoming a challenge with numerous reports and publication mechanisms out there. Its exceeding challenging to review each output for PI/SI information. There is a lot of reliance on people to do the right thing.

5. Talent development - With new tools and technology coming in each day from various tech companies, it’s a constant challenge to develop and grow talent within the org. Sometimes, people are reluctant, and sometimes the missions are reluctant.  

Talent Retention - Due to high market demand and low quality supply of talent, clubbed with company's financial targets, retention becomes challenging.

What would be the proudest or most enjoyable moment in your analytics career?

During the initial days of my career, I was enamoured by the power of databases and telling the story of performance and movement behind it via visuals. The Technology was over-engaging and I took my own time to savour the achievements and slowly step into management. 

I have had many proud moments in learning new skills and delivering value to the business via dashboards and intelligent reports. But as I joined new organisations, the data has grown exponentially and there has been a lack of organising it for better use. My proudest moments were born from solving that problem, when I take the lead in organizing & cataloguing the metadata for the enterprise or larger business units. It's an area that helps enterprises have better control with curation rather than creation of similar assets. I have a unique ability to bring structure to federated data using semantic layer that is business friendly and support self-service! 

It gives me utmost satisfaction and pride when the new analysts are able to spend time on the actual work rather than data ingestion and transformation. 

What advice would you give to a woman wanting to get into the analytics industry?

A lot of women inherently have a mathematical and logical bent of mind. 

1. Analyzing for self and others is natural to most women i.e. playing out scenarios. Analytics is about applying the math and stat to everyday business scenarios using the new age tools and techniques. So, get some tools training from easily available platforms, 

2. Speak to some industry friends or contacts via Linkedin to understand what is involved and just get in. 

3. There are a number of public data and sites available to experiment and try your hands. Be bold and go for it. Publish some of your work to get public review. 

4. There are various job sites that describe what the industry is expecting for the role. Unpack some of those skills and learn them. 

5. A formal education in Business Analytics will be extremely useful if you have the time for it.  

In terms of the future of analytics, what do you think will be the most interesting aspect/s?

The next decade is about Data dominance, until it normalizes.

1. True self-serve analytics - Significant reduction in time to market insights - especially with Natural language processing and generative AI trends and tools picking up, making it easier to navigate the data sets, aid with quicker analysis and insights for the common person. 

2. Increased Diversity and inclusion - The nature of analytics and access to tools will drive people from diverse backgrounds to be involved in this space.

3. Data Privacy and security - A greater emphasis on identification and protection while we will also see an increased attack on such information. 

4. Increased real-time collaboration with third party data - Compute power and new analytics tools will make it easier to source and combine company information with multiple third party data alerting customers/business reliably. 

5. The Fear - Traceability and logic behind decisions may be further lost as these tools will become more black-boxed.