Data Management

Whose fingerprints are all over your customer data?

The appeal of going into the lake is strong u2013 but many have a blind spot when it comes to sensitive data.

How to fix the data integration mess

Once you've admitted there's a problem, it's time to figure out how to get started fixing it.

The CIO’s data dilemma: The paradox of plenty?

Classical data strategies have focused on "what the data looks like" and can it provide "answers." Newer approaches provide the ability to move beyond that to "how can I use what I have" and can it provide "directio

Back to the (SQL) Future, Part 3

In the first post in this series, I discussed the emergence of NoSQL to address the need to make databases compatible with cloud needs. And in my last blog post, I talked about the dichotomy between smart databases and smart applications. I asked whe

Three lines of defense for data management

Three lines of defense for data management

Firms are considering data risk in their group risk appetite statements. Here's how to build three lines of defense for data management and data risk.

Simpler applications and smarter databases, Part 2

Here's a more detailed look into the trade-offs represented by NoSQL.

Chief data officers are moving from defense to offense

An MIT conference panel reveals a shift in thinking toward big data regulatory and compliance reporting, and the expanding role of the CDO in the board room.

10 hot data analytics trends — and 5 going cold

Big data, machine learning, data science u2014 the data analytics revolution is evolving rapidly. Keep your BA/BI pros and data scientists ahead of the curve with the latest technologies and strategies for data analysis.

The promise and payoff of NoSQL, Part 1

As we move toward a new industry view of data management, we are also moving towards a world in which smarter databases will enable simpler applications. In this first installment of a 3-part blog series, letu2019s take a look at where weu2019ve bee

Data governance in the world of “data everywhere”

With data sources, uses and solutions on the rise, data governance is becoming even more important. But what are the phases of a successful and scalable data governance program?