Creating value in the Data-Driven Economy: Careers in Digital, Big Data & Analytics

Earlier this year, I had the opportunity to speak at a Big Data workshop organized as part of the 'National Business & Technology Conference' held at the Toronto Board of Trade. The audience comprised of several graduating students from various colleges in and around Toronto interested in careers in technology, especially in areas of Digital, Big Data & Analytics. The students had numerous questions about opportunities in these areas and how they could capitalize on these. What follows here is a compilation of what I shared with the audience.

Let me start off by sharing my perspective on what these trends mean, and then address how someone can consider jobs that might be applicable to their interests and background. Keep in mind that there are multiple ways of defining the scope of these areas, and what I am sharing here is one individual's view based upon their experiences.

What are these trends?

First off all, let's assess what drives these trends. 

Our world, as we know it, is changing fast to more of a self-service, on-demand paradigm. Consumerization of technologies through smart-phones and other connected devices are changing how we operate as individuals on a day to day basis. More and more people are using smartphone apps for shopping, searching for information, messaging, video calling and a million other uses that are a far cry from the original use, i.e. making phone calls. As we consume and generate varied types and greater amount of data, the organizations we interact with are investing to capture this data and interpret it accurately to understand our needs as customers. 

Within this construct, 'Big Data' is the type of data, 'Digital' is how the data is captured or generated, and 'Analytics' is how organizations sift through the data to make sense of it. This is an oversimplification of these terms, but it'll serve the purpose for now.

Let's elaborate on these briefly:

Digital

The simplest definition covers both internal or external touch-points from an organization's perspective for capturing and sharing of data. The concept of 'Digital' has to be viewed through the lens of its multiple iterations.

The first iteration was when most data was generated internally within organizations, and information exchange with customers, suppliers, and other external stakeholders was primarily through analog paper based methods. Data management technologies like spreadsheets and relational database management systems were the product of this era.

The second iteration was when the Internet became a part of the business landscape, which led to more data being captured and exchanged through technology rather than paper. This gave birth to technologies like web-based input via forms, and the emergence of websites as a preferred form of information exchange with external stakeholders. Technologies like Java, .NET, & HTML are some products of this era.

We are currently in the third iteration largely driven by the mobile paradigm. A lot of the business is being conducted on the go, and it becomes imperative to capture additional metadata around the location of the transactions to develop a better context. At the same time, the emergence of social media platforms like Facebook and Twitter have created new avenues for individuals to express their demographic and psycho-graphic preferences. However, unlike the organization-controlled platforms of the earlier era, most of these platforms are outside the control of any single company.

What this means from a company's perspective is that they have to change their current business processes, as well as embed more of a technology focus into their operating model in order to make the most of these trends.

Considering the speed and variety of new technology solutions that are popping up, IT departments across the world have been struggling with how to create new capabilities within the constraints of their existing budgets. The 'Cloud' paradigm has come to the rescue, allowing technology solutions to be used on a 'pay-as-you-go' model, thus avoiding the need to make significant investments in technology acquisition.

Big Data

Big Data is characterized by the 3V's -

• Variety - Type & nature of data, e.g.- Structured(Text), and Unstructured(Images, Audio and Video) content
• Volume - Quantity of data being generated, e.g.- the large number of tweets, Facebook posts or Instagram photos being generated by millions of people
• Velocity - The speed at which the data is being generated, e.g.- By some estimates, every minute, 100 million emails, 100,000 tweets and almost 700,000 Facebook posts are generated

Additional elements of Big Data include Veracity, Variability & Value.

Technologies like Hadoop and NoSQL are synonymous with Big Data since they allow organizations to create megastores of data for simpler storage & processing.

Analytics

From the perspective of an organization that is now looking at multiple incoming and outgoing data pipes, as well as different types of data flowing through them, the challenge becomes - how does one make sense of all this information, and then present the insights in an easy to understand manner for an executive audience's decision making? For this purpose, different approaches have come to prominence.

The use of statistical modeling has become quite prevalent to identify the most important variables to analyze, while removing noise; as well to identify patterns in data that are not evident through the use of conventional technologies. Some of the technologies like SAS, R and Python have become more widespread in their use, as organizations evolve from a reporting/business intelligence paradigm to a more insights driven one.

Technologies like QlikView and Tableau have been front-runners in helping organizations create Visualization capabilities to simplify the consumption of complex insights, along with introducing Data Discovery features to promote the exploration of patterns within data.

The organization's perspective

Let's look at the impact of all of these trends from the perspective of an organization, as an example, your local library system.

The Problem

The library system is having financial challenges due to budget cuts related to its municipal funding. It must decide how to manage its costs and make investments that will continue to create value for its customers over the new few years. Most of its historical investments have been made in maintenance of physical buildings, purchase of media(books,etc.) and paying the salaries of staff like librarians. However, the challenge is that the library is seeing a lot more media rental being done online, and foot traffic to its physical locations is dropping. Most of the people using the library are coming either to attend the occasional cultural program, or use wi-fi. Most of the librarians are either sitting around doing nothing, or at best, performing administrative tasks. The municipal government is asking for a clearer idea of what investments the library is planning as well as the value that is being created for the city residents.

The Identified Solution

The library has identified that the following steps need to be taken -

1) Data Capture - Existing manual or paper based processes need to be automated so that it is capturing more information about resident preferences and requirements. More surveys need to be conducted to understand resident program usage and demand. This needs to be done in a mobile friendly manner.

2) Insight Generation - From existing online data as well as newly captured data, media rental and browsing patterns of residents need to be analyzed to identify topics of interest for program design as well as guiding future media purchases. These insights need to be driven with the least possible technology investment.

3) Operating Model changes - Based upon insights generated, staffing model needs to be changed. New staff need to be hired and existing staff need to be retrained or re-assigned to different tasks to align with the insight-driven strategic direction.

The individual's career perspective

Assuming you as a new or existing staff member, what does this really mean for you in terms of your career? How do you get on the bandwagon of these new and exciting trends?

First off, lets establish how comfortable you are with technology. I'm approached by a number of people regularly who want to get on the bandwagon of Digital, Big Data or Analytics but do not feel they have the technology background. For those people, there are plenty of options available on the business or functional side of things. If you are someone who can understand the People/Human Resource angle, or the Business Process Automation angle, or the coordination through Governance, there is a role for you. When it comes to Digitizing a process, understanding the business value of Big Data, or driving insights using Analytics, it requires a team of business and technology people working together to get to the outcome. If you are someone who has skills from a domain perspective, whether it be in the area of Customer, Finance, Workforce, Supply Chain or Risk, then you be invaluable from a model creation and process re-engineering perspective.

Assuming you are someone who is more technical in nature, you have to identify where your strengths and interests lie from an architecture perspective. Are you the Data Engineer who focuses more on the click-stream data or the operational systems that act as data sources, or for that matter sensors and instrumentation that is generating data by the second? Maybe you are an Integration expert, focusing on the Extraction, Transformation & Loading of data? You could be the Data Modeler who spends their time primarily on data storage activities, whether that be in RDBMS or Data Warehouses. If you are someone with an Art or Design background, maybe you could be the Data Artist on the team turning out fantastic visualizations. And of course, let's not forget all you statistical modelers and math geeks who are the future Data Scientists. If the organization is lucky, you could be a Programmer who can traverse more than one of the above mentioned areas.

There are so many technologies that are prevalent in all of these areas that is impossible to have an informed discussion on which ones are more suitable from a training perspective without understanding the specific context of an industry or domain.

But the gist is - This is a growing field and with the introduction of new concepts on a daily basis, continues to be an exciting place for individuals to build their career while creating value for the world out there. I'm excited by all the opportunities and hope that you are too! All the best!

Love it? Hate it? Are there other topics you would like to hear about? Leave a comment below!

Disclaimer:The ideas shared here are the thoughts and opinions of the author and do not in any shape or form reflect the position of the author's employer, Accenture.