Data Management

Data Management news, analysis, research, how-to, opinion, and video.

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Oracle pitches autonomous capabilities for its entire cloud platform

Oracle is raising its bid to attract enterprises moving to the cloud by extending AI-based automation throughout its PaaS (platform as a service) offerings, claiming that the new automated services will cut costs and reduce...

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4 data analytics trends that will dominate 2018

As businesses transform into data-driven enterprises, data technologies and strategies need to start delivering value. Here are four data analytics trends to watch in the months ahead.

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Snowflake, now a unicorn, eyes global growth for cloud data warehouse

Fueled by a capital injection of $263 million making it the first cloud-native data warehouse startup to achieve "unicorn" status, Snowflake is set this year to expand its global footprint, offer cross-regional, data-sharing...

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Data is not the new oil or the infrastructure of the digital economy

Some are claiming that data is the “new oil.” Some claim that data is infrastructure. Both of these assertions are false.

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The unexpected benefits of data analytics

Data analytics can uncover surprising insights that lead to unexpected new program or product ideas, as these six real-world examples show.

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5 ways big data will shake up supply chain systems

Big data analytics can provide visibility into where things are, where they should be, and what’s gumming up the system.

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Choosing a smarter metaphor for your data governance strategy

Organizations want to be “data-driven.” The gist of which is they want people using data to make decisions. Leaders know that too many people make stuff up. And every leader has done it themselves, so it’s not as if it’s a secret...

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The future is now: 2018 market predictions for database and data management

While these types of end-of-the (or beginning-of-the) year lists have become commonplace, it’s still important to constantly evaluate the changes we are seeing, and understand where they will take us next.

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Why data governance?

Data governance used to be a nice to have, but due to the increasing focus and importance of data and analytics, it’s becoming a necessity that helps to drive data management across the enterprise.

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Data agility or scale: a false choice?

A successful marketplace should be able to provide both agility and scale.

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The ghosts of Christmas retail: data management past, present and yet to come

It’s never too late to do something about your regrets and wake up to a happier, data-fueled Christmas.

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Sherlock Holmes – the original enterprise architect?

Sherlock Holmes had a keen ability to see minute details often overlooked by other investigators, but also possessed a unique capability to stitch together clues and apply context to arrive at the correct answers that eluded others.

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12 myths of data analytics debunked

From data concerns to staffing needs to technology combinations, data analytics misconceptions abound. Here’s a no-bull look at how to leverage data science to deliver bona fide business results.

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What is DataOps? Collaborative, cross-functional analytics

DataOps (data operations) is an emerging discipline that brings together DevOps teams with data engineer and data scientist roles to provide the tools, processes and organizational structures to support the data-focused enterprise.

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IS ETL dead? In the age of AI, not quite

It's just more complex, harder and significant.

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Intelligent image and video management for the enterprise

As image and data quality goes up – driven by better capture, transfer, processing and compressing technologies – the ability to store and process these images and video data easily becomes a competitive advantage.

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What’s the difference between a chief data officer, chief digital officer, and chief analytics officer?

Companies are increasingly developing new executive roles aimed at making the organization as a whole more data-driven and digitally adept. Here’s how three new tech exec titles take different approaches to tackling the same problem.

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Why your BI strategy needs a universal semantic data layer

A universal semantic data layer is a single business representation of all corporate data aimed at helping users access data using common business terms via the BI and analytics tools of their choice.

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