AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

Octopai

JANUARY 8, 2020

You can’t do this easily without automated data lineage tools. Octopai’s metadata discovery and management suite provides visualization tools that empower you to see and report everything about sensitive customer data. Octopai's Automated Metadata Management Platform can make CCPA compliance a breeze.

Metadata 54

Metadata Key Performance Indicator OLAP Forecasting 54

Jet Global

JUNE 5, 2019

But data alone is not the answer—without a means to interact with the data and extract meaningful insight, it’s essentially useless. Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. OLTP vs OLAP. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing).

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Jet Global

DECEMBER 1, 2020

Truly efficient and effective reporting requires a BI engine capable of organizing and preprocessing large data sets and managing replication with operational data sources. In addition, it can be very helpful to have a metadata layer in place that can help non-developers make sense of the information in the database.

Finance 78

Finance Data Warehouse OLAP Reporting 78

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Less data gets decompressed, deserialized, loaded into memory, run through the processing, etc.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Jet Global

SEPTEMBER 22, 2023

However, the complexity of Microsoft Dynamics data structures serves as a roadblock, making it difficult to use Power BI without a proper connection to your data. Dynamics ERP systems demand the creation of a data warehouse to ensure fast query response times and that data is in a suitable format for Power BI.

Visualization 52

Visualization Reporting Data Warehouse OLAP 52