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The future of data: A 5-pillar approach to modern data management

CIO

This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process. Operational errors because of manual management of data platforms can be extremely costly in the long run.

Data 167
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What is data analytics? Analyzing and managing data for decisions

CIO

More specifically: Descriptive analytics uses historical and current data from multiple sources to describe the present state, or a specified historical state, by identifying trends and patterns. In business analytics, this is the purview of business intelligence (BI). Data analytics vs. business analytics.

Analytics 203
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No-code business intelligence service y42 raises $2.9M seed round

TechCrunch

.” Before y42, Vietnam-born Dang co-founded a major events company that operated in over 10 countries and made millions in revenue (but with very thin margins), all while finishing up his studies with a focus on business analytics. And that in turn led him to also found a second company that focused on B2B data analytics.

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Achieving Business Analytics Success

Datavail

The data indicate high success for enterprises that use data to develop their corporate strategies and then implement them into winning business operations. Datavail’s data engineers, analysts and systems management teams can help your organization find its brightest future by deploying business intelligence solutions.

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What Do CIOs Have To Know About Business Intelligence?

The Accidental Successful CIO

Understanding Business Intelligence vs. Business Analytics. Business intelligence tools provide insights into the current state of the business or organization: where are sales prospects in the pipeline today? It also gets to the heart of the question of who business intelligence is designed for.

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Forget the Rules, Listen to the Data

Hu's Place - HitachiVantara

However, in the rush to do this, many of these systems have been poorly architected to address the total analytics pipeline. A Big Data Analytics pipeline– from ingestion of data to embedding analytics consists of three steps Data Engineering : The first step is flexible data on-boarding that accelerates time to value.

Data 90
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How Much Should I Be Spending On Observability?

Honeycomb

These are going to require us all to learn some slightly different skillsto think about data management in different ways; ways more like how business analytics teams are accustomed to managing their data than the way ops teams do. Over the long run, I think observability is moving towards a data lake type model.