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Embracing Data Mesh: A Modern Approach to Data Management

Data Virtualization

Reading Time: 2 minutes In the ever-evolving landscape of data management, one concept has been garnering the attention of companies and challenging traditional centralized data architectures. This concept is known as “data mesh,” and it has the potential to revolutionize the way organizations handle.

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Building a data team at a mid-stage startup: a

Erik Bernhardsson

The backdrop is: you have been brought in to grow a tiny data team (~4 people) at a mid-stage startup (~$10M annual revenue), although this story could take place at many different types of companies. I guess I should really call this a parable.

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Data – The Lifeblood of Intelligence Automation


It’s not new news and it doesn’t need to be complicated; it’s just a revolution of how we leverage data! Let’s take a quick dive into the data-driven universe of AI (i.e., This article breaks down how data powers intelligence automation. intelligence automation).

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How to Prepare for Data Scientist Interview in 2023?

The Crazy Programmer

One of the fastest-growing domains in the recent years is data science. For those who don’t know, data science revolves around different subjects that ultimately lead to one goal. Organizing and explaining this data for strategic planning is what a data scientist does and should be skilled at.

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Modern Data Architecture for Embedded Analytics

Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind. Expert guidelines for a high-performance, analytics-ready modern data architecture.

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Unlocking the Potential of Data for your Business: A Quick Guide to Ideation Sessions for Data Science


Are you struggling to identify the best data science opportunities for your organization? Combine business, data and IT experts, and balance seniority to assure you focus on a valuable and feasible business problem. Create a driver tree or sketch the impacted business process to identify where data science can potentially help.

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Data Mesh Accelerate Workshop

Martin Fowler

Over the last couple of years, we've been helping several enterprises use the Data Mesh approach to managing analytical data. Shifting thinking to Data Mesh isn't easy, it changes how teams are organized, how work is prioritized, and what technologies to apply.

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5 Things a Data Scientist Can Do to Stay Current

Demand for data scientists is surging. With the number of available data science roles increasing by a staggering 650% since 2012, organizations are clearly looking for professionals who have the right combination of computer science, modeling, mathematics, and business skills. Collecting and accessing data from outside sources.

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6 Steps to More Streamlined Data Modeling

Discover a streamlined methodical approach to Apache Cassandra® data modeling. Are you a developer, database architect, or database administrator that's new to Cassandra, but been tasked with developing a plan for implementing the technology anyway? Worry no more.

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4 Approaches to Data Analytics

The world of data analytics is changing fast as organizations look to gain competitive advantages through the application of timely data.

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Data Science Fails: Building AI You Can Trust

The new DataRobot whitepaper, Data Science Fails: Building AI You Can Trust, outlines eight important lessons that organizations must understand to follow best data science practices and ensure that AI is being implemented successfully. Download the report to gain insights including: How to watch for bias in AI.

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Monetizing Analytics Features: Why Data Visualization Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Download the whitepaper to learn about Monetizing Analytics Features, and Why Data Visualizations Will Never Be Enough. Five years ago they may have. But today, dashboards and visualizations have become commonplace.

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10 Rules to More Streamlined Data Modeling

Apache Kafka is a powerful piece of software that can solve a lot of problems. Like most libraries and frameworks, you get out of it what you put into it. Learn 10 rules that will help you perfect your Kafka system to get ahead.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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How Banks Are Winning with AI and Automated Machine Learning

Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Brought to you by Data Robot.