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Where are AI Investments Going in 2024?

The conference will cover data science and AI trends, tools, and techniques.
Partnerships in organizing events can enhance the quality and participation.

How to Shift from Data Science to Data Engineering

There is a high demand for skilled data engineers.
Data scientists can transition into data engineering due to transferable skills.

What Does a Data Engineering Job Involve in 2024?

Data engineers play a crucial role in collecting, storing, and processing data for analysis and decision-making.
Data integration is a key responsibility of data engineers, involving combining data from multiple sources into a single, usable format.

Spark Starter Guide 4.13: Importing Data from a Relational Database (MySQL)

Relational databases are vital for operational data but can also hold valuable analytics data.
Spark simplifies accessing databases to populate Spark DataFrames for analysis.

Announcing the First Speakers for the 2024 Data Engineering Summit

Data-centric AI enables improving models without code changes
Apache Arrow and Parquet allow fast analytic operations and interoperability.

Are All Monoliths Bad?

Monolith vs. Microservices: Complexity and team size influence architecture choice.

Where are AI Investments Going in 2024?

The conference will cover data science and AI trends, tools, and techniques.
Partnerships in organizing events can enhance the quality and participation.

How to Shift from Data Science to Data Engineering

There is a high demand for skilled data engineers.
Data scientists can transition into data engineering due to transferable skills.

What Does a Data Engineering Job Involve in 2024?

Data engineers play a crucial role in collecting, storing, and processing data for analysis and decision-making.
Data integration is a key responsibility of data engineers, involving combining data from multiple sources into a single, usable format.

Spark Starter Guide 4.13: Importing Data from a Relational Database (MySQL)

Relational databases are vital for operational data but can also hold valuable analytics data.
Spark simplifies accessing databases to populate Spark DataFrames for analysis.

Announcing the First Speakers for the 2024 Data Engineering Summit

Data-centric AI enables improving models without code changes
Apache Arrow and Parquet allow fast analytic operations and interoperability.

Are All Monoliths Bad?

Monolith vs. Microservices: Complexity and team size influence architecture choice.
moredata-engineering

Accenture looks to bolster AI capabilities with Redkite acquisition

Accenture acquires data consultancy Redkite to enhance data and AI capabilities

Job Vacancy: (Senior) Big Data Engineer * // GameDuell | IT / Software Development Jobs | Berlin Startup Jobs

GameDuell is a leading casual gaming company in Germany with over 130 million registered players worldwide.
They are looking for a (Senior) Big Data Engineer to build and maintain their Big Data infrastructure.

Microsoft and Databricks try to sew up the data platform

Microsoft Fabric is being hailed as one of Microsoft's biggest data product launches since SQL Server.
Fabric offers data engineering, data lakes, data warehousing, machine learning, and AI on a single platform.
Competitors like Snowflake and Google are catching up quickly in the race to offer similar features and capabilities.

Spark Tutorial: Master the Essential Skills for Data Engineering and Data Science

Spark has become the defacto tool for big data processing.
Understanding and mastering Spark is crucial for data engineering and data science job interviews.

Managing Missing Data in Analytics - DATAVERSITY

Today, corporate boards and executives understand the importance of data and analytics for improved business performance.
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