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What is Microsoft Fabric and Why Should You Care?

Datavail

The Microsoft Fabric announcement at Microsoft Build 2023 has caused quite a stir in the data and analytics world. Microsoft Fabric is an all-in-one analytics solution that brings together seven Azure services on a shared SaaS foundation, in a unified experience combined with AI. Both structured and unstructured data are supported.

Azure 52
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Trends in Cloud Jobs In 2019

ParkMyCloud

In addition, they also have a strong knowledge of cloud services such as AWS, Google or Azure, with experience on ITSM, I&O, governance, automation, and vendor management. Business Intelligence Analyst. BI Analyst can also be described as BI Developers, BI Managers, and Big Data Engineer or Data Scientist.

Trends 72
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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.

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

Altexsoft

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Data availability. ELT vs ETL.

Tools 52
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What is Data Pipeline: Components, Types, and Use Cases

Altexsoft

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. Data pipeline components. When do you need a data pipeline?

Data 76
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Implementing a Data Management Strategy: Key Processes, Main Platforms, and Best Practices

Altexsoft

Data integration and interoperability: consolidating data into a single view. Specialist responsible for the area: data architect, data engineer, ETL developer. Scattered across different storages in various formats, data values don’t talk to each other. Snowflake data management processes.

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Data Lakehouse: Concept, Key Features, and Architecture Layers

Altexsoft

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Data lake architecture example. Poor data quality, reliability, and integrity.