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Become More Data-Driven by Evolving Analytics Workloads

CIO Business Intelligence

Some examples include: Customer 360 analytics, retail inventory and sales analysis, manufacturing operational analysis, eCommerce fraud prevention, network security intelligence, data warehouse consolidation and discount pricing optimization. Just starting out with analytics?

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The top 15 big data and data analytics certifications

CIO Business Intelligence

AWS Certified Data Analytics The AWS Certified Data Analytics – Specialty certification is intended for candidates with experience and expertise working with AWS to design, build, secure, and maintain analytics solutions. The exam consists of 40 questions and the candidate has 120 minutes to complete it.

Big Data 126
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Understanding BI Tools in Today’s Market

Smarten

How Do We Define Business Intelligence Today? Business Intelligence (BI) is the lifeblood of an organization. As the Business Intelligence solution market evolves, it may be difficult for an organization to know when to invest in these tools, and which tools are best for enterprise and user needs.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119
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Your 5-Step Journey from Analytics to AI

CIO Business Intelligence

One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Another option is a data warehouse, which stores processed and refined data. Set up unified data governance rules and processes.

Analytics 115
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Unlock The Power of Your Data With These 19 Big Data & Data Analytics Books

datapine

And shows how big data and the advances in analytical technologies are shaping the way the world is perceived. 2) Designing Data-Intensive Applications by Martin Kleppman. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz.

Big Data 263
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The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t

CIO Business Intelligence

And to give employees access to the data they need, organizations will need to move away from legacy systems that are siloed, rigid and costly to new solutions that enable analytics and AI with speed, scalability, and confidence. Just starting out with analytics? Find out more about Intel advanced analytics. [1]

Analytics 137