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.

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 Data Warehouse is Dead, Long Live the Data Warehouse, Part II

Data Virtualization

Reading Time: 4 minutes My previous post explained that, in my mind, the data lakehouse differs hardly at all from the traditional data warehouse architectural design pattern (ADP).

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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How to Build Data Experiences for End Users

Organizational data literacy is often addressed, but it’s uncommon to consider users’ data literacy levels when building products. Product managers need to recognize their end users' data literacy when building an application with analytic features.

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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Is Data Virtualization the Secret Behind Operationalizing Data Lakes?

Data Virtualization

Reading Time: 4 minutes The amount of expanding volume and variety of data originating from various sources are a massive challenge for businesses. In attempts to overcome their big data challenges, organizations are exploring data lakes as repositories where huge volumes and varieties of.

Data Minimization as Design Guideline for New Data Architectures

Data Virtualization

IT excels in copying data. It is well known organizations are storing data in volumes that continue to grow. However, most of this data is not new or original, much of it is copied data. For example, data about a.

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.

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.

Modern Data Architecture for Embedded Analytics

Data has gone from a mere result of applications & processes to being crowned king. Picking the right avenue to data architecture depends on your organization’s needs. Development teams should build in stages, starting with a task that can be solved.

Data Science for Dummies

Dataiku

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

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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.

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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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

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6 Steps to More Streamlined 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. Discover a streamlined methodical approach to Apache Cassandra® data modeling.

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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Data Pre-Processing Using SageMaker Data Wrangler – Part 1

Cloud That

What is Amazon SageMaker Data Wrangler? Amazon SageMaker Data Wrangler Core Functionalities. Data Transformation using SageMaker Data Wrangler. What is Amazon SageMaker Data Wrangler? Amazon SageMaker Data Wrangler Core Functionalities. TABLE OF CONTENT.

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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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Data Fabrics, Data Meshes and the role of Data Virtualisation

Data Virtualization

The post Data Fabrics, Data Meshes and the role of Data Virtualisation appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

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Drive Better Decision-Making with Data Storytelling

Embedded Analytics can be the foundation of successful applications, and data storytelling is now critical for business today. It has become pivotal to drive decisions, generate actionable insights, and increase user adoption and stickiness.

Data Fabric Approach for Effective Data Management

Data Virtualization

Reading Time: 4 minutes A discussion on All Things Data with Katrina Briedis, Senior Product Marketing Manager (APAC) at Denodo, with a special focus on Data Fabric Approach for Effective Data Management.

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Is Cloud Data Integration the Secret to Alleviating Data Connectivity Woes?

Data Virtualization

Reading Time: 3 minutes Many businesses are moving towards a cloud-based approach in terms of managing their data, but that doesn’t mean that incorporating the cloud into businesses is an easy process. The post Is Cloud Data Integration the Secret to Alleviating Data Connectivity Woes?

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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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.

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.

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.

8 Languages for Data Science

TechBeacon

The data keeps coming. The job of a data scientist is to turn all of those endless bits into coherent analysis so that data users can begin to look for answers in the sea of information. Enterprise IT, Data Management, Data Science

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2021 Data/AI Salary Survey

O'Reilly on Data

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.

Difference between Data Warehousing and Data Mining

The Crazy Programmer

Data warehousing and data mining are two popular and essential techniques to store and analyze data. Data warehousing refers to the compiling and organizing of the stored data in the company’s database. What is Data Warehousing? What is Data Mining?

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Monetizing Analytics Features: Why Data Visualization Will Never Be Enough

Five years ago, data visualizations were a powerful way to differentiate a software application. Today, free visualizations seem to be everywhere. Two trends are forcing application providers to rethink how they offer analytics in their products.

Introducing the Liquid Data Model

Data Virtualization

Reading Time: 2 minutes In the software world, we constantly represent real phenomena in abstract terms, and this is no exception in the world of data storage. We say that data storage, like matter, adheres to the Law of Increments, which states that, according.

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GoDataFest 2022: Google Cloud Data Platform Workshop

Xebia

This blog explores the various sessions throughout those 3 days but specifically focuses on the Cloud Data Platform workshop on Friday the 28th. . GoDataFest features a multitude of sessions focused on various data technologies and platforms.

Difference between Data and Information

The Crazy Programmer

As a result of data that has been evaluated to give a logical meaning, information satisfies the needs of a user, providing it importance and utility. Data comes from a Latin word called Datum, which means “something given.” Data has become the plural of datum throughout time.

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Data Virtualization and Data Science

Data Virtualization

If we look at a typical , many of its stages have more to do with data than science. Before data scientists can begin their work regarding data science, they often must begin by: Finding the right data Gaining access.

The Hitchhiker’s Guide to Embedded Analytics – 4 Mission-Critical Steps to Take on Your Analytics Journey

The right analytics capabilities will turn data into valuable insights for your end users. This research-based guide, derived from insights of industry professionals, will allow you to create an optimal strategy for acquiring those capabilities.

Where Does Your Data Go?

DevOps.com

One of the most interesting developments in security and compliance in recent years is the ability to follow a piece of data through an application from input to consumption and see each bit that touches it. The post Where Does Your Data Go?

When Data Virtualization Makes the Difference

Data Virtualization

In a previous post, I talked about some key data virtualization concepts and the types of professionals who can benefit the most from it. Data virtualization is not only beneficial in certain specific areas, but it can really make a.

What is Data Virtualization? Understanding the Concept and its Advantages

Data Virtualization

Reading Time: 3 minutes Data is at the center of every company. The post What is Data Virtualization? Understanding the Concept and its Advantages appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Management Challenges for the Modern Enterprise

Data Virtualization

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

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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?)