Enterprise Analytics Trends

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Evan Terry, Chief Analytics Officer at Velocity Mortgage Capital said that enterprise analytics technology is increasingly sophisticated, due to machine learning, artificial intelligence (AI), and streaming analytics, but you can’t benefit from these advancements without a solid foundation. “There’s a real interplay there between the foundational and the advanced.” Terry discussed these interplays during his Trends in Enterprise Analytics presentation at the DATAVERSITY® Enterprise Analytics Online Conference.

Balancing Act

Terry talked about the balance of chaos and order in business,and he sees creativity and organization as playing interrelated parts in achieving that balance. People who lean toward creativity and openness are imaginative, insightful, curious, and able to embrace the unknown. People who tend toward the conscientious side are thoughtful, goal-directed, detail-oriented, and enjoy organization and planning.

Creative people are very good at starting things, he said, whether it’s starting companies, or building or launching products, or creating innovative teams.

“On the other side, you’ve got the conscientious folks who are typically very good at coming into something like that brand new idea, and then figuring out how to make it all work in practice.”

This balance between creativity and openness exists within business, but then also “connects directly to what we’re doing in an analytics context.”

Problem Solving and Personality

In the context of analytics, a high degree of openness is best for finding new solutions, and a high degree of conscientiousness is best for developing solutions. Strong enterprise analytics need both, he said.

Analytics trends follow these success factors:

  • Openness: New approaches, technologies, territories, and questions
  • Conscientiousness: Focus on reliability, repeatability, and a strong foundation

Two Meta-trends for Analytics

Terry identified two overarching trends for analytics: what he calls the “Brilliant Basics” and the “Exciting Extras.” The basics focus on building a solid foundation in fundamental areas such as data, staffing, and organization. The extras explore adding value through AI/machine learning, new methods for interfacing with data, and new platforms and core technology:

“The trick here is to always be embracing the new technologies, but embracing them in a way that will allow you to demonstrate business value, and essentially justify whatever expense you need to spend, whether it be on technology or people, in order to make that happen.”

The Trends

The Brilliant Basics are driven by conscientiousness, and are tactical, foundational, and focused on operations. Data Governance, the office of the Chief Data Officer (CDO), Data Quality Management, and staffing all fall under this trend, he said. The Exciting Extras are driven by openness, and support capability, and visionary strategies. Cloud-First technologies, embedded and collaborative Business Intelligence (BI), artificial intelligence, natural language processing, and conversational user interfaces fall under this trend. Terry went on to elaborate on the concepts under each trend.

Brilliant Basics —Data Governance

“We’ve been talking about Data Governance for a long time, but it’s still something that is a challenge for a lot of organizations.” Questions such as “What data is useful?” “Where can I find it?” and  “How do I organize it?” are still a concern. Better understanding of data lake management has kindled new interest in Data Governance as well.

General Data Protection Regulation (GDPR) requires answers to the questions “Who can access the data?” “Where is it stored?” “How is it used?” “When you start talking about regulatory cloud, you start to talk about some potentially really significant issues with impacting business.”

  • What Can You Do About This Trend?

Terry suggests an evaluation of exposure to regulatory action, asking, “How bad is it if we don’t have a handle on this? How bad could it be?” as well as devising a strategy for creating a culture of data literacy.

Brilliant Basics — The Function of the CDO

Terry believes the trend toward recognizing the importance of the CDO arises in part from the growing number of organizations putting this role into place. He quoted figures from a 2018 article by Microstrategy entitled Six Statistics Shaping the Role of Chief Data Officer, which reported that 57 percent of enterprise organizations now have a Chief Data Officer, and 24 percent are considering creating a Chief Data Officer position.

The CDO role drives data literacy across the enterprise, influences a data-driven culture, and can play a key role in creating value and generating revenue. “There’s a sense that there’s some value out there. There are some issues coming up that really require a notion of data literacy across the enterprise.”

  • What Can You Do About This Trend?

It’s important to create a culture where people understand data’s role in the enterprise. “Your first priority should be to drive that creation and adoption of a data culture,” which could come from top down or bottom up.Put into practice, that could look like having a data dictionary, or access to analytics and data, or literacy about what the data actually means. “I think if you’ve got these kinds of basics right, you’ll be successful later on,” he said.

Brilliant Basics — Data Quality Management

Data Quality issues can impact the accuracy of analytics when data is missing or inaccurate, and with the advent of streaming analytics, Data Quality errors or problems can no longer be fixed in a batch overnight. Quality issues can also cause inconsistent output and increased processing time, and can ultimately cause the company to make bad decisions, he said. “You need to be on top of these problems early,” he said.

  • What Can You Do About This Trend?

Leverage the tools within Data Governance processes, such as alerts and algorithms to detect anomalous data and

report back to business users. “And again, always draw it back to the value that you’re creating.”

Brilliant Basics — Strategic Staffing and Talent

Terry said there is enormous demand forecasted for Data Science employees, and that the supply of college graduates will not keep up with that demand. The MIT Sloan Management Review reported that 40 percent of companies struggle with finding and retaining the right talent, and IBM, in their report The Quant Crunch: How the Demand for Data Science Skills is Disrupting the Job Market, predicts there will be 2.7 million jobs for all U.S. data professionals by 2020, an increase of 364,000 jobs.

Demand for data scientists, developers, and data engineers will reach nearly 700,000 openings. The report goes on to say that machine learning, Big Data and Data Science skills are the most challenging to recruit for and, if not filled, can potentially create the greatest disruption to ongoing product development and go-to-market strategies.

In a 2017 Gallup Poll conducted by the Business-Higher Education Forum, by 2021 69 percent of employers expect candidates with Data Science and analytics skills to get preference for jobs in their organizations, yet only 23 percent of college and university leaders say their graduates will have those skills.

  • What Can You Do About This Trend?

Terry recommends establishing channels with local colleges for recruiting, creating positions that show an analytics career path, and managing the analytics environment to attract top talent.

“Analytics is very competitive. If you’ve got all of the components from the data, to the people, to the culture, to the processes all nailed down, now you can really talk about doing some exciting things with more advanced capabilities.”

Exciting Extras — Cloud-First Technologies

Scalable cloud-based storage for enterprise data lakes can now expand to cloud-based analytics for rapidly changing environments. This is an area where Terry sees an opportunity to try out new technologies and approaches, in a way that comes with reduced costs and faster time-to-market. In some instances, built-in analytics capabilities may be included as well.

  • What Can You Do About This Trend?

There is renewed focus on cloud-based data lakes, and the value that they’re generating. “I think there’s got to be some real success stories that you can point to, with your data lakes in general. But I think when you’re in the cloud, again, you’ve potentially got that additional argument to make.”

Exciting Extras — Embedded and Collaborative BI

Enabling the use of analytics in all facets of the business increases the visibility and access to data for all users within the organization. Terry said there is a “huge push” from users for embedded access to analytics, and the end result is very powerful. “Maybe the environment needs to come to the users, instead of the users coming to the environment.”

  • What Can You Do About This Trend?

Organizations should evaluate where analytics can be leveraged in operations, and determine how cloud can maximize built-in analytics, sharing, and presentation mechanisms, he said. “From an embedded and collaborative standpoint, I think there’s a real move toward making analytics more accessible.”

Exciting Extras — Artificial Intelligence (AI)

AI enables the adoption of more sophisticated predictive analytics. Self-modifying, machine learning algorithms can refine predictive performance, creating feedback loops to inform future algorithms.

  • What Can You Do About This Trend?

Terry recommends not waiting to start on predictive analytics, and at the same time, don’t underestimate the difficulty level, technical and non-technical, including acceptance of the concept.

“You don’t need a PhD in statistics to do some predictive work. . . if you do a little bit of reading, and a little bit of analysis, you’re going to find that you can make great advances in terms of your ability to predict certain kinds of things that may end up providing you that business value.”

Exciting Extras —Voice and Natural Language

Voice for data input, such as Siri, Alexa, or Google Home, expands the reach of analytics to a broader audience, and reduces the costs of interacting with the data, becoming the next step in self-serve analytics.

  • What Can You Do About This Trend

The business use cases for voice and natural language he considers a little bit more aspirational, but textual parsing may be useful. Some people without the skill to craft a properly formed query may be able to work with language-based requests. Keep in mind that natural language, as well as AI and predictive analytics may not be a culture fit, he said.

Where Do You Go from Here?

Establish or reconfirm analytics strategy with an eye toward operational efficiency, new sources of business, and better decision-making. Build a solid foundation for progress with the Brilliant Basics and then evaluate how the Exciting Extras can add value to your organization. “This is the value chain, if you will, of the BI world, and we’re really strengthening all of those components simultaneously, and trying to improve them all simultaneously.”

Want to learn more about DATAVERSITY’s upcoming events? Check out our current lineup of online and face-to-face conferences here.

Here is the video of the Enterprise Analytics Online Presentation:

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