Next-Generation Data Warehouses
CIO Review|October 2019
Picture a situation like this: you are collecting and analyzing insights about product sales performance.
Gautam Gupta
Next-Generation Data Warehouses

The results make you wonder why a certain area in your organization is doing better than others. You slice, deep-dive, judge, and use different perspectives to analyze and to conclusions, but can’t find the answers.

You need data to arrive at decisions but that is not available in your corporate systems. How do you access this information and quickly analyze it all to be able to make intelligent business choices?

Bring Analytics to Data

Organizations face the tough business reality of today – of bringing together people, processes, and data for a balanced approach, especially when it comes to data and analytics. The real work begins when organizations can take advantage of existing on-premise data and invest in analytics technology that creates a path to the future as more data and things shift to, and are born in, the cloud.

If users don’t want to go the traditional route of specifying and uploading and testing data, they’d need a whole new way to integrate data from on-premises and cloud sources, in other words, they require the next-generation modern data warehousing.

A typical analytics wish-list can include:

• Ability to remodel the data warehouse on demand

• Access to the data source while on the move

• Avoid duplication of data

• Evade loss of time with data-load jobs

• Facilitate analytical processing in real-time

• Decrease of data objects to be stored and maintained

Introduction to Next-Generation Data Warehouse

Diese Geschichte stammt aus der October 2019-Ausgabe von CIO Review.

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Diese Geschichte stammt aus der October 2019-Ausgabe von CIO Review.

Starten Sie Ihre 7-tägige kostenlose Testversion von Magzter GOLD, um auf Tausende kuratierte Premium-Storys sowie über 8.000 Zeitschriften und Zeitungen zuzugreifen.

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