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Challenges in replacing SSRS with Microsoft Power BI

BizAcuity

SSRS is a server-based reporting platform that comes free with SQL Server 2012. Microsoft Power BI is a business analytics tool, which is a collection of apps, connectors, and software services that work together to turn unrelated sources of data into coherent information. Migrating SSRS 2012/2014/2016 to Power BI is fine.

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A Guide To The Methods, Benefits & Problems of The Interpretation of Data

datapine

In fact, a Digital Universe study found that the total data supply in 2012 was 2.8 More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. Prior to 2012, Intel would conduct over 19,000 manufacturing function tests on their chips before they could be deemed acceptable for release.

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Challenges in replacing SSRS with Microsoft Power BI

BizAcuity

SSRS is a server-based reporting platform that comes free with SQL Server 2012. Microsoft Power BI is a business analytics tool, which is a collection of apps, connectors, and software services that work together to turn unrelated sources of data into coherent information. Migrating SSRS 2012/2014/2016 to Power BI is fine.

article thumbnail

Challenges in replacing SSRS with Microsoft Power BI

BizAcuity

SSRS is a server-based reporting platform that comes free with SQL Server 2012. Microsoft Power BI is a business analytics tool, which is a collection of apps, connectors, and software services that work together to turn unrelated sources of data into coherent information. Migrating SSRS 2012/2014/2016 to Power BI is fine.

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The Future Of The Telco Industry And Impact Of 5G & IoT – Part 1

Cloudera

The current scale and pace of change in the Telecommunications sector is being driven by the rapid evolution of new technologies like the Internet of Things (IoT), 5G, advanced data analytics, and edge computing. In many established markets, traditional sources of revenue are either plateauing or declining relatively rapidly. .

IoT 66
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Convergent Evolution

Peter James Thomas

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

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Data Science, Past & Future

Domino Data Lab

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. Those workflows would feedback into your business analytics. Transcript.