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Data APIs: Realizing the Future of Data Warehousing

DevOps.com

Data is the currency of business in today’s digital economy, with organizations collecting mountains of data from their customers, products and services. Enterprises are increasingly turning to data warehouses to store this valuable enterprise data and to make it useful and actionable.

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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.

Data 699
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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. – AltexSoft All the data processing is done in Big Data frameworks like MapReduce, Spark and Flink.

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The Data Lakehouse Myth

Data Virtualization

Reading Time: 2 minutes The data lakehouse attempts to combine the best parts of the data warehouse with the best parts of data lakes while avoiding all of the problems inherent in both. However, the data lakehouse is not the last word in data.

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Modern Tech and More: Empowering Your Supply Chain for Success

Speaker: Cory Skinner, Founder and CEO of FactR

Ready to dive into new tech to protect your supply chain, but not sure where or how to start? In this webinar, Cory Skinner, Founder and CEO of FactR, will break down the new, innovative technologies and strategies that you can implement to mitigate historic challenges, and even teach you what NOT to do along the way!

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The Data Warehouse is Dead, Long Live the Data Warehouse, Part I

Data Virtualization

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. Reading Time: 4 minutes “Le roi est mort, vive le roi.”

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The Key Components of a Successful Data Lake Strategy

Data Virtualization

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository.

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How to Simplify Your Approach to Data Governance

Data Virtualization

Reading Time: 6 minutes Data Governance as a concept and practice has been around for as long as data management has been around. It, however is gaining prominence and interest in recent years due to the increasing volume of data that needs to be.

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Choosing a Data Catalog: Data Map or Data Delivery App?

Data Virtualization

Reading Time: 5 minutes Today, many applications call themselves “data catalogs.” The idea seems, on the face of it, easy to understand: a data catalog is simply a centralized inventory of the data assets within an organization. Data catalogs also seek to be the.

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Data Ecology

Data Virtualization

Reading Time: 3 minutes We are naturally inclined to think that our relationship with data develops solely in the world > data > use direction, in which data captures what happens in the world, and we use data to understand events in the world.

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How King Crushes New Product Development using Data-Driven Insights

Speaker: Ian Thompson, Head of Business Intelligence at King, and Zara Wells, Strategic Customer Success Manager at Looker

Product Managers looking to leverage data to make informed product design decisions can learn a lot from renowned gaming company King, maker of Candy Crush and many other games - even if their product has seemingly no overlap with games. Don't miss King’s data expert (dare we say king?)

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Why Data Mesh Needs Data Virtualization

Data Virtualization

Data mesh” is a new data analytics paradigm proposed by Zhamak Dehghani, one that is designed to move organizations from monolithic architectures such as the data warehouse and the data lake to more decentralized architectures.

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Why Data Mesh Needs Data Virtualization

Data Virtualization

Data mesh” is a new data analytics paradigm proposed by Zhamak Dehghani, one that is designed to move organizations from monolithic architectures such as the data warehouse and the data lake to more decentralized architectures.

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Data engineers vs. data scientists

O'Reilly Media - Data

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers. Overly simplistic venn diagram with data scientists and data engineers. Yes, both positions work on big data.

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From Data Swamp to Data Lake: Data Zones

Perficient

This is the final blog in a series that explains how organizations can prevent their Data Lake from becoming a Data Swamp, with insights and strategy from Perficient’s Senior Data Strategist and Solutions Architect, Dr. Chuck Brooks.

Data 109
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The Unexpected Cost of Data Copies

This paper will discuss why organizations frequently end up with multiple data copies and how a secure "no-copy" data strategy enabled by the Dremio data lake service can help reduce complexity, boost efficiency, and dramatically reduce costs.

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From Data Swamp to Data Lake: Data Catalog

Perficient

This is the second blog in a series that explains how organizations can prevent their Data Lake from becoming a Data Swamp, with insights and strategy from Perficient’s Senior Data Strategist and Solutions Architect, Dr. Chuck Brooks.

Data 108
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5 Trends in Financial Services That Will Change How You Think about Your Data

Data Virtualization

The post <strong>5 Trends in Financial Services That Will Change How You Think about Your Data</strong> appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

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From Data Swamp to Data Lake: Data Classification

Perficient

This is the third blog in a series that explains how organizations can prevent their Data Lake from becoming a Data Swamp, with insights and strategy from Perficient’s Senior Data Strategist and Solutions Architect, Dr. Chuck Brooks. Low sensitivity data—intended for public use.

Data 109
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2021 Data/AI Salary Survey

O'Reilly Media - Ideas

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. The average salary for data and AI professionals who responded to the survey was $146,000. The average annual salary for employees who worked in data or AI was $146,000.

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Gartner Report - Introducing DataOps Into Your Data Management Discipline

Data teams are increasingly under pressure to deliver data to support a range of consumers and use cases. DataOps techniques can address the data delivery challenges through a more agile and collaborative approach to building and managing data pipelines.

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Denodo Achieves AWS Data and Analytics ISV Competency

Data Virtualization

Reading Time: 3 minutes The Denodo Platform, which simplifies data management with real-time data access across myriad different data sources, can be flexibly installed on-premises or in the cloud, as a cloud-native implementation, to enable a wide range of use cases.

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From Data Swamp to Data Lake: Data Quality

Perficient

This is the third blog in a series that explains how organizations can prevent their Data Lake from becoming a Data Swamp, with insights and strategy from Perficient’s Senior Data Strategist and Solutions Architect, Dr. Chuck Brooks.

Data 106
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From Data Swamp to Data Lake

Perficient

For several years now I have heard people that wanted to slow the progress of companies becoming data-driven use the term “Data Swamp”, usually without much understanding of what a Data Swamp is. Given this definition, I want to point out that a data swamp is not necessarily bad.

Data 109
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Healthy Data

O'Reilly Media - Ideas

Neither is being “data driven.” The first survey looked at the use of data. Whether or not that’s healthy in and of itself, it suggests that there isn’t yet any consensus about the role data plays. The bane of data science has been the HIPPO: the “highest paid person’s opinion.”

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Ultimate Guide to the Cloud Data Lake Engine

This guide describes how to evaluate cloud data lake engine offerings based on their ability to deliver on their promise of improving performance, data accessibility, and operational efficiency as compared with earlier methods of querying the data lake.

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Implementing Data-Driven DevSecOps

DevOps.com

The post Implementing Data-Driven DevSecOps appeared first on DevOps.com. Application Performance Management/Monitoring Blogs Continuous Delivery Continuous Testing DevSecOps IT Security data analysis devsecops mobile application testing mobile security software security

Data 135
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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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Data Mesh vs Data Fabric: Understanding the Key Differences

Data Virtualization

Reading Time: 2 minutes In recent years, there has been a growing interest in data architecture. One of the key considerations is how best to handle data, and this is where data mesh and data fabric come into play.

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SQL Streambuilder Data Transformations

Cloudera

SQL Stream Builder (SSB) is a versatile platform for data analytics using SQL as a part of Cloudera Streaming Analytics, built on top of Apache Flink. It enables users to easily write, run, and manage real-time continuous SQL queries on stream data and a smooth user experience.

Data 113
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12 Considerations When Evaluating Data Lake Engine Vendors for Analytics and BI

Businesses today compete on their ability to turn big data into essential business insights. Modern enterprises leverage cloud data lakes as the platform used to store data. 57% of the enterprises currently using a data lake cite improved business agility as a benefit.

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The Future of Data Strategy

Data Virtualization

But do you wonder what the future of data strategy looks like? Data exploration and analysis can bring enormous value to a business. The post The Future of Data Strategy appeared first on Data Virtualization blog.

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Modern Data Architecture: Data Warehousing, Data Lakes, and Data Mesh Explained

Data Virtualization

Reading Time: 3 minutes At the heart of every organization lies a data architecture, determining how data is accessed, organized, and used. For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.

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Data Science for Dummies

Dataiku

"How can you work with data scientists? Data Basics FeaturedYou never liked math!".

Data 98
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New-Age Tech and Culture Driving Data Democratization

DevOps.com

Data democratization has become critical for organizations to leverage data’s true value and fully realize its benefits. Making data available across the organization helps companies to serve customers better and make data-driven decisions that align with their goals and objectives.

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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.

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The Data Lakehouse: Blending Data Warehouses and Data Lakes

Data Virtualization

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one?

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Data Lake vs Data Warehouse

The Crazy Programmer

Companies everywhere are handling more data than ever and all these terabytes of data need to be stored somewhere. Should you store the data in a database, a data warehouse, or a data lake? What is Data Lake? Querying a Data Lake. Data Lake.

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SaaS Data Backup and the API Bottleneck

DevOps.com

The need to protect SaaS data has never been greater. A recent global survey from Odaseva found that 51% of ransomware attacks are targeting SaaS data, and they are more likely to succeed (52%) than were attacks on cloud, endpoint and on-premises data.

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Is Data the New Oil?

Data Virtualization

Reading Time: 2 minutes A recent post, on the cost and impact of persisted data, got me thinking: If data is the new oil, as some believe, then data virtualization is akin to the electrification of gas/petrol-powered cars.

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Top Considerations for Building an Open Cloud Data Lake

In this paper, we explore the top considerations for building a cloud data lake including architectural principles, when to use cloud data lake engines and how to empower non-technical users.