Remove Data Science Remove Data Warehouse Remove OLAP
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Comparison between Online Processing Systems: OLTP Vs OLAP

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In the field of Data Science main types of online processing systems are Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP), which are used in most companies for transaction-oriented applications and analytical work.

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What Are OLAP (Online Analytical Processing) Tools?

Smart Data Collective

Data science is both a rewarding and challenging profession. One study found that 44% of companies that hire data scientists say the departments are seriously understaffed. Fortunately, data scientists can make due with fewer staff if they use their resources more efficiently, which involves leveraging the right tools.

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Database vs. Data Warehouse: What’s the Difference?

Jet Global

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

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How to Build a Performant Data Warehouse in Redshift

Sisense

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).

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How OLAP and AI can enable better business

IBM Big Data Hub

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

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What are decision support systems? Sifting data for better business decisions

CIO Business Intelligence

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

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What is business intelligence? Transforming data into business insights

CIO Business Intelligence

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. Increased competitive advantage: A sound BI strategy can help businesses monitor their changing market and anticipate customer needs.