The Missing Piece - Diving into the World of Big Data with .NET for Apache Spark

The Missing Piece - Diving into the World of Big Data with .NET for Apache Spark

Data is growing at an unprecedented amount with both human generated and machine generated data. Come, learn about the open-source, .NET for Apache Spark project, the same technology that teams such as Office, Dynamics and Azure use widely to process 100s of Terabytes of data inside Microsoft.

#dotnet #spark #apache-spark #programming #developer

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Big Data Tools 1.0 Generally Available | The Big Data Tools Blog

A new update of the Big Data Tools plugin has been released. This is our first version for general use, after a year and a half of the Early Access Preview program.

Install the plugin from the JetBrains Plugin Repository or from inside your IDE to edit Zeppelin notebooks, upload files to cloud filesystems, and monitor Hadoop and Spark clusters. The following JetBrains IDEs support the plugin: IntelliJ IDEA Ultimate, PyCharm Professional Edition, and DataGrip.

In this release, we’ve added many useful features and addressed a variety of bugs. Let’s dive into the details.

#big data tools #newsletter #plugins #releases #apache #apache spark #apache zeppelin #big data #big data tools #precode #python #spark #spark-submit #zeppelin

Big Data Tools 1.0 Generally Available

A new update of the Big Data Tools plugin has been released. This is our first version for general use, after a year and a half of the Early Access Preview program.

Install the plugin from the JetBrains Plugin Repository or from inside your IDE to edit Zeppelin notebooks, upload files to cloud filesystems, and monitor Hadoop and Spark clusters. The following JetBrains IDEs support the plugin: IntelliJ IDEA Ultimate, PyCharm Professional Edition, and DataGrip.

In this release, we’ve added many useful features and addressed a variety of bugs. Let’s dive into the details.

#big data tools #newsletter #plugins #releases #apache #apache spark #apache zeppelin #big data #big data tools #precode #python #spark #spark-submit #zeppelin

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Big Plans for Big Data and .NET for Spark | .NET Blog

The .NET for Apache Spark team is approaching a major milestone as we plan to reach version 1.0 later this year. We want to provide the best possible experience for working with big data from .NET. We’re looking into how you work with big data and .NET for Spark to help us prioritize the right features, scenarios, and solutions for upcoming releases. You can help!

#.net #.net core #apache #big data #spark for .net #data science

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