Data has become the lifeblood of modern enterprises. However, past conversations with CIOs revealed a dramatic range of data and predictive analytics maturity from organization to organization. So during a recent CIOChat I tried to get a better understanding of the state of business intelligence (BI) and data lakes, given that Harvard Business School Professors Marco Iansiti and Karim Lakhani have proclaimed this “the age of artificial intelligence (AI).” Are CIOs and their organizations ready?

Where Are CIOs With Their BI and Data Lake Efforts?

To my surprise, CIOs have made big strides in the last couple of years. They get that BI on its own does not directly impact future results or financial returns. Instead, they see the game today being about real-time predictive analytics, even in higher education. CIO David Seidl said, “data lakes and predictive analytics have become a place where we can make a positive difference in student success, enrollment and other outcomes for the people we serve.” However, CIO Sharron Pitt said, “real-time business modeling should not ignore long-term trends in industries that don't live by the minute. Retail has to understand peak periods. Higher Education needs to understand year-to-year enrollment. In higher education, mandated enrollment reporting requires history. But now enrollment trending is required for survival, so predictive analytics are critical.”

Does the Term BI Still Have Relevance?

While the overarching business intelligence term is still fine, CIOs want to incorporate machine learning models, AI techniques and more real-time approaches into the definition. “Of course we need BI. Like the Coke commercial says — it's an and, not an or we need BI and new techniques. We still need the data, the analysis and the measures and metrics we get out of our BI to stay smart and on top of things,” Seidl said. “I think that’s right, based on the Venn diagram of the two pretty closely overlapping,” agreed chief digital officer Jay Brodsky.

Former CIO, Tim McBreen, summarized by saying, “both BI and machine learning have relevance today and for the future. Historical data can provide basic and predictive AI for key planning.”

“Do you ever feel like we're doing something more like a data water tower? We filter the data, we make sure it meets our standards, and then we try to pump it to the areas that need it in a consumable way,” said Seidl. “Data Lakes are great for jumping into, but ... there's another model. Clearly as robots take over the world, BI will still have relevance in planning, decision-making and storytelling.”

Related Article: Why Business Intelligence Has a Role in the World of AI

What Considerations Are Most Important in the Data Era?

There are multiple answers to this question, but here is a summary of the most common answers from CIOs:

Learning Opportunities

  1. Data quality/data integrity.
  2. Data governance/data privacy/data security.
  3. Data culture/data understanding/data management.
  4. Golden record/collection purposes/golden record access control.
  5. Data integration/data provenance/where the data comes from/who owns it/ethical uses of data.
  6. Data agility/the CI/CD for the flow of data.

At the end of the day, whether CIOs are talking about traditional BI, analytics, machine learning or data lakes, success comes from a well-executed data governance program. Data quality, integrity and priority really matter. For this reason, it is time to repair enterprise data holes.

Related Article: Good Data Governance in the Platform Age

How Can CIOs Work With CDOs to Ensure Data Projects Succeed?

When an organization has a chief data officer (CDO) it is important to work collaboratively with them and other leaders within the organization. Together, CIOs and CDOs can define, articulate and execute the overall data strategy for the business. In doing so, it is important CIOs be a barrier breaker and a supporter of their organization’s CDO. Together CIOs and CDOs can build data governance at the right level for the organization. They can also champion data and stay aware of what data can do for the organization. Finally, together they can build a data culture at the C-level — and change habits. In this process, it is important to listen, learn, align, deliver and repeat.

Related Article: Chief Data Officer Enters v4.0: What Does That Mean?

CIO's New Role: Data Champion

The CIO should become an organizational data champion regardless of whether there is a CDO. So much depends on getting data right. All organizations need governance. It is time to fix data that needs fixing. Clearly, CIOs would agree with Tom Davenport who said in his book "Analytics at Work," “You can’t be really good at analytics without being really good at data.” CIOs may not be data scientists, but they can help ensure the quality of data created and that data is made useful.

fa-solid fa-hand-paper Learn how you can join our contributor community.