Remove 2020 Remove Data Warehouse Remove Marketing Remove OLAP
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CCPA 2020: Getting Your Data Landscape Ready

Octopai

From California’s new data privacy law going into full effect to potential new U.S. federal data privacy laws on top of an alphabet soup of global laws and regulations, the name of the game for 2020 is going to be “compliance.”. The California Consumer Privacy Act (CCPA) came into effect on January 1, 2020.

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Navigating Data Entities, BYOD, and Data Lakes in Microsoft Dynamics

Jet Global

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

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Reporting System: Everything You Need to Know

FineReport

Top 10 Free and Open Source Reporting Tools in 2020. For popular reporting tools on the market, you can refer to: Best Reporting Tools List in 2020 and How to Choose. Based on the process from data to knowledge, a standard reporting system’s functional architecture is shown below.

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Why Business Intelligence is Top of Mind for CFOs for 2022

Jet Global

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. This will ensure that you have the information you need to optimize your marketing spend. The Future Is Now.

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Master Your Power BI Environment with Tabular Models

Jet Global

The size and scope of business databases have grown as ERP functionality has evolved, businesses have increased their adoption of CRM and marketing automation, and collaboration networks have become more common. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications.

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What Is Embedded Analytics?

Jet Global

Section 2: Embedded Analytics: No Longer a Want but a Need Section 3: How to be Successful with Embedded Analytics Section 4: Embedded Analytics: Build versus Buy Section 5: Evaluating an Embedded Analytics Solution Section 6: Go-to-Market Best Practices Section 7: The Future of Embedded Analytics Section 1: What are Embedded Analytics?