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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. The authors state that the target audience is technical people and, second, business people who work with technical people. Nevertheless, I strongly agree.

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Ascend.io lands $31M to automate data pipeline orchestration

TechCrunch

The company’s platform is designed to give data teams a unified platform to automate the orchestration of data engineering and analytics workloads, he says, ideally reducing the need for manual configuration. Rather, it was the ability to scale the productivity of the people who work with data.

Data 230
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Enhancing the Business Strategy with Data Engineering Solutions

Trigent

To do this, they are constantly looking to partner with experts who can guide them on what to do with that data. This is where data engineering services providers come into play. Data engineering consulting is an inclusive term that encompasses multiple processes and business functions.

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5 hot IT hiring trends — and 5 going cold

CIO

Firms that want to innovate and grow while headcounts are in flux are looking to upskill talent from within , promote their firm’s strengths to prospective candidates, and broaden their pool of potential hires from nontraditional backgrounds. And again, the solution for organizations is a focus on the ability to adapt. “By

Trends 327
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Making AI Work in Legal Tech: Balancing Cost and Performance

Invid Group

The legal sector has been traditionally conservative, but in recent years, it has embraced AI integration and innovation advantages. By automating data processes, organizations can ensure that insights and models are consistently applied to new data and operational decisions, reducing manual effort and improving responsiveness.

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5 hot IT budget investments — and 2 going cold

CIO

Fifty-two percent of organizations plan to increase or maintain their IT spending this year, according to Enterprise Strategy Group. This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%).

Budget 363
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The Future of the Data Lakehouse – Open

Cloudera

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. The cloud native table format was open sourced into Apache Iceberg by its creators.

Data 97