The “How” Behind Big Data Analytics – Interview With Neil Chandler, Gartner Research VP

Neil Chandler

Neil Chandler – Gartner VP of Research

 

Answering the “how” questions behind analytics

Neil Chandler, a research VP from Gartner, the world’s leading information technology research and advisory company, is one of the confirmed speakers at  #drivenbydata Summit that will happen at Level 39, One Canada Square the coming 20th of March. This is a quarterly Summit that will discuss issues concerning Big Data & Analytics developments. Neil Chandler has a long experience in the field of business intelligence and his talk at the event promises to set the scene for the day, and answer some of the “how” questions regarding value & culture of Analytics. IntelligentHQ interviewed Neil Chandler about his unique views concerning this topic:

1. Could you introduce yourself and tell us a bit about your background?

I am Neil Chandler, a Gartner Research VP. My main focuses are on business intelligence, analytics and performance management. This includes writing about and advising organizations about market trends, vendors, service providers and best practices. I have more than 20 years of experience in strategic product marketing, project management and implementation projects in the field of business intelligence, corporate performance management and information systems. I joined Gartner in 2006.

2. Can you tell us about your experience working for Gartner?

I have a leading position in driving Gartner’s research into business analytics and performance management incorporating modeling, metrics, scorecards, strategy management and corporate performance management.

3. What will you bring to the #drivenbydata Summit?

I intend to focus on the driving forces behind analytics and help to answer some of the more difficult “how” questions. In my opinion too much of the conversation around Analytics is related to “what” questions regarding technology & architecture and not enough consideration is given to the “how” questions regarding value & culture.

4. In your opinion what are the most important challenges and opportunities presented by Big Data and the Internet of Things concerning business?

The most important considerations around new or disruptive technologies should be concerning how do we utilise them to drive increase efficiency, drive growth, reduce risks and foster innovation. Analytics enables the harnessing of the ever increasing volumes, velocity and variety of information to make smarter business decisions that help run, grow and transform our businesses.

5. What is / are the biggest misconception(s) about big data in your view?

Big Data is not new. Big Data is a technology, not a solution.

6. Big data forces business to wrestle key strategic and operational challenges. What do you propose as the best ways to deal with these challenges?

Managing the increasing user demands arising from new and more extensive sources of information, and more powerful analytic capabilities, requires a shift not only in technology, but also in people, skills, processes and business alignment. However, many IT functions have yet to make the transition required for the IT department to become a suitable organization to support business analytics.

7. How can one harness massive troves of consumer information most effectively?

We need to mature in our strategies for Information and Analytics.  We need to focus on the business outcomes and values rather than the technology that supports them. Business must understand that data-driven strategies are especially beneficial when considering how to leverage existing data assets (such as big data and other systems of record), whereas value-driven approaches are beneficial for focusing on strategic goals.

8. There’s a difference between data science and data intelligence. How do you see this?

This is a question of semantics.  The real issue is that organizations need to adopt more sophisticated uses of analytics and there is a shortage of available skills. To close this gap vendors are developing easier to use analytics to enable more users to self-service and this gives rise to an increased pool of producers.  However, some use cases and business problems will still require complex and sophisticated approaches beyond the capability of the average citizen and that is where the data scientists will gravitate.

9. Big data is causing enterprises to find new ways to leverage information sources to drive growth. What are your suggestions?

Big data analytics is the technical solution to the convergence of forces around social, information, mobile and cloud. Convergence is turning enterprises into information & value-driven companies, and mature big data analytics is a way to get there. The interplay of data, analytics, information governance and information quality with respect to these forces is the deciding factor for big data analytics success.

10. How can you use big data analytics or large and complex datasets to predict future customer behaviors, trends and outcomes?

Organizations need to recognise that just adding more data is not going to necessarily get them any nearer to their business goals.  We must harness the data with analytics.  So therefore, the key step is to employ a range of analytic solutions orientated to a number of business areas around customer and profitability, sales performance, marketing effectiveness, and so on.  Through the application of analytics we will derive the benefits of more information.

big data heat map by industry Gartner

Big Data heat map by industry Gartner

11. What are the biggest trends you see regarding Enterprise Information Management?

EIM is a discipline of its own.  EIM enables people from across the enterprise to share, manage and reuse information that was created in different applications and stored in different databases and repositories. But these capabilities do not help the enterprise by themselves. Leaders must design their EIM initiative so that sharing and reusing information creates business value, and the value created must contribute to enterprise goals.

12. How do you separate the full scope of big data and data from social media?

Data is a resource that must be managed.  Whether it comes from internal or external sources and in an array of formats.  Different forms of data provide support for different types of questions for different types of users and use cases. Some data may support factual analysis and some may provide supporting context.  An information strategy is needed to help organizations figure out how to leverage all forms of information in appropriate and effective ways.

13. With the amount of data increasing every day and doubling how do you the future of hyper data and the necessary simplification?

If the question is “how do businesses sustain an information and analytics capability given the exponential rise and use of information” then my answer is through disruptive change.  We need to put analytics and fact-based decision making at the centre of the business.  These changes may require a cultural shift, they may need new roles such as chief data and Analytics officers, new tools such as data discovery and predictive analytics, new teams such as citizen data scientists and analytics centres of excellence, and new bi-modal information approaches to support infrastructure modernization as well as innovation.

how to map who you are