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What is a Data Pipeline?

Jet Global

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

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Oracle Cloud Migration FAQs Answered by Angles

Jet Global

What are the best practices for analyzing cloud ERP data? How can we respond in real time to the company’s analytic needs? Data Management. How do we create a data warehouse or data lake in the cloud using our cloud ERP? How do I access the legacy data from my previous ERP? Self-service BI.

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The Right Tool to Support Your Microsoft Dynamics Migration

Jet Global

When migrating to the cloud, there are a variety of different approaches you can take to maintain your data strategy. Those options include: Data lake or Azure Data Lake Services (ADLS) is Microsoft’s new data solution, which provides unstructured date analytics through AI. More than Excel.

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Unlocking Trino’s Full Potential With Simba Drivers for BI & ETL

Jet Global

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

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Do the Benefits of Cloud Outweigh the Costs?

Jet Global

What are the best practices for analyzing cloud ERP data? How can we respond in real time to the company’s analytic needs? Data Management How do we create a data warehouse or data lake in the cloud using our cloud ERP? How do I access the legacy data from my previous ERP?

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SAP BPC Alternatives: Which One is Right for You?

Jet Global

The other preferences that users expect from modern business performance management solutions are company-wide planning, increased planning frequency, increased insights, operational reporting, strategic alignment, and predictive forecasting. data lakes & warehouses like Cloudera, Google Big Query, etc.,

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