Remove Data Cleanse Remove Data Lake Remove Raw Data Remove Relational Database
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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. 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. What is a data lake?

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DataOps Architecture: 5 Key Components and How to Get Started

Databand.ai

In a DataOps architecture, it’s crucial to have an efficient and scalable data ingestion process that can handle data from diverse sources and formats. This requires implementing robust data integration tools and practices, such as data validation, data cleansing, and metadata management.

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Power BI Developer Roles and Responsibilities [2023 Updated]

Knowledge Hut

The role of a Power BI developer is extremely imperative as a data professional who uses raw data and transforms it into invaluable business insights and reports using Microsoft’s Power BI. Develop a long-term vision for Power BI implementation and data analytics. Who is a Power BI Developer?

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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

Technical Data Engineer Skills 1.Python Python Python is one of the most looked upon and popular programming languages, using which data engineers can create integrations, data pipelines, integrations, automation, and data cleansing and analysis. ETL is central to getting your data where you need it.

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ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

AltexSoft

It is a data integration process with which you first extract raw information (in its original formats) from various sources and load it straight into a central repository such as a cloud data warehouse , a data lake , or a data lakehouse where you transform it into suitable formats for further analysis and reporting.

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

ProjectPro

You have probably heard the saying, "data is the new oil". It is extremely important for businesses to process data correctly since the volume and complexity of raw data are rapidly growing. Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics.

BI 52
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Big Data Analytics: How It Works, Tools, and Real-Life Applications

AltexSoft

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. Data storage and processing. Data cleansing.