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Top ETL Use Cases for BI and Analytics:Real-World Examples

ProjectPro

Over the past few years, data-driven enterprises have succeeded with the Extract Transform Load (ETL) process to promote seamless enterprise data exchange. This indicates the growing use of the ETL process and various ETL tools and techniques across multiple industries.

BI 52
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What is Data Extraction? Examples, Tools & Techniques

Knowledge Hut

Database Queries: When dealing with structured data stored in databases, SQL queries are instrumental for data extraction. ETL (Extract, Transform, Load) Processes: ETL tools are designed for the extraction, transformation, and loading of data from one location to another.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined.

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Data Marts: What They Are and Why Businesses Need Them

AltexSoft

Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit. On the other hand, independent data marts require the complete ETL process for data to be injected. Hybrid data marts.

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Turning Streams Into Data Products

Cloudera

During a customer workshop, Laila, as a seasoned former DBA, made the following commentary that we often hear from our customers: “Streaming data has little value unless I can easily integrate, join, and mesh those streams with the other data sources that I have in my warehouse, relational databases and data lake.

Kafka 86
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IBM InfoSphere vs Oracle Data Integrator vs Xplenty and Others: Data Integration Tools Compared

AltexSoft

The tool supports all sorts of data loading and processing: real-time, batch, streaming (using Spark), etc. ODI has a wide array of connections to integrate with relational database management systems ( RDBMS) , cloud data warehouses, Hadoop, Spark , CRMs, B2B systems, while also supporting flat files, JSON, and XML formats.

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Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation

AltexSoft

Today, companies want their business decisions to be driven by data. But here’s the thing — information required for business intelligence (BI) and analytics processes often lives in a breadth of databases and applications. So, the tool you’re about to choose must support the required data format.