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 549

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.

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.

Data-Driven Performance Feedback Helps Teams Improve Customer Outcomes

Speaker: Mickey Mantle, Founder and CEO at Wanderful Interactive Storybooks | Ron Lichty, Consultant: Interim VP Engineering, Author, Ron Lichty Consulting, Inc.

In this webinar Mickey Mantle and Ron Lichty will teach you why its important to have data driven performance reviews, the most effective way to use data in performance reviews, and how this data helps to align your employee proficiency with your company goals.

Go Fast Using Data Virtualization

Data Virtualization

Reading Time: 3 minutes During a recent house move I discovered an old notebook with metrics from when I was in the role of a Data Warehouse Project Manager and used to estimate data delivery projects. For the delivery a single data mart with.

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.

Go Fast and Far Using Data Virtualization

Data Virtualization

Reading Time: 3 minutes We are always focused on making things “Go Fast” but how do we make sure we future proof our data architecture and ensure that we can “Go Far”?

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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Data pipeline components are just normal applications

Xebia

A data pipeline component is nothing more than a normal application. Example data pipeline: ELT. The artifact is then run as part of your data pipeline. Connectivity to other systems/data sources. Apply the principle of least-privilege to your data pipeline components.

The Importance of PCI Compliance and Data Ownership When Issuing Payment Cards

This eBook provides a practical explanation of the different PCI compliance approaches that payment card issuers can adopt, as well as the importance of both protecting user PII and gaining ownership and portability of their sensitive data.

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.

Data 193

Modernize Your Data Architecture with Data Virtualization

Data Virtualization

Practically overnight, organizations have been forced to adapt by modernizing their data architecture to support new types of analysis and new ways to connect to data. The post Modernize Your Data Architecture with Data Virtualization appeared first on Data Virtualization blog.

Modernize Your Data Architecture with Data Virtualization

Data Virtualization

Practically overnight, organizations have been forced to adapt by modernizing their data architectures to support new types of analysis and new ways to connect to data. The post Modernize Your Data Architecture with Data Virtualization appeared first on Data Virtualization blog.

Rebranding Data

O'Reilly Media - Ideas

We’re living that now, but for naming the data field. ” “Big Data.” ” “Data science.” Case in point: machine learning used to be considered part of data science; now it’s seen as a distinct (and superior) field. Data Signal

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4 Approaches to Data Analytics

As the analytics landscape continues to evolve, application teams who need to embed dashboards, reports, and other analytics capabilities in their applications can choose from dozens of solutions. How do you differentiate one solution from the next?

Does Your Organization Need a Data Diet?

DevOps.com

The scenario is all-too-familiar: There’s a security breach, and afterward, the affected organization asks what it must do to better protect its data. Often, the best defense against an embarrassing and costly breach is to collect only data that […].

Weaving Architectural Patterns III – Data Mesh

Data Virtualization

Reading Time: 4 minutes Software systems designers often structure their thinking around the underlying functional and data/information components of their desired applications.

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.

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.

Weaving Architectural Patterns III – Data Mesh

Data Virtualization

Reading Time: 4 minutes Software systems designers often structure their thinking around the underlying functional and data/information components of their desired applications.

Go Fast and Far Using Data Virtualization to help you Go Fast and Go Far

Data Virtualization

Reading Time: 3 minutes We are always focused on making things “Go Fast” but how do we make sure we future proof our data architecture and ensure that we can “Go Far”?

Data Mesh Principles and Logical Architecture

Martin Fowler

Last year, my colleague Zhamak Dehghani introduced the notion of the Data Mesh , shifting from the notion of a centralized data lake to a distributed vision of data.

Weaving Architectural Patterns: I – Data Fabric

Data Virtualization

Since its first incarnation almost 35 years ago in my IBM Systems Journal article, the data warehouse (DW) has remained a key architectural pattern for decision-making support. The post Weaving Architectural Patterns: I – Data Fabric appeared first on Data Virtualization blog.

Make Payment Optimization a Part of Your Core Payment Strategy

Everything you need to know about payment optimization – an easy-to-integrate, PCI-compliant solution that enables companies to take control of their PSPs, minimize processing costs, maximize approval rates, and keep control over their payments data.

Weaving Architectural Patterns: I – Data Fabric

Data Virtualization

Since its first incarnation almost 35 years ago in my IBM Systems Journal article, the data warehouse (DW) has remained a key architectural pattern for decision-making support. The post Weaving Architectural Patterns: I – Data Fabric appeared first on Data Virtualization blog.

Rapidly Enable Tangible Business Value through Data Virtualization (Data minimization)

Data Virtualization

The post Rapidly Enable Tangible Business Value through Data Virtualization (Data minimization) appeared first on Data Virtualization blog. Uber owns no fleet, and Airbnb owns no real estate.

Data Observability: Data Management Best-Practice

HALEY TEEPLES

The best practices and methodologies to manage data quickly

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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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2021 State of Analytics: Why Users Demand Better

As organizations become more data driven, their analytics requirements grow. Find out how knowledge workers use analytics and explore their needs and preferences.

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.

Different Types of Data Transmission

The Crazy Programmer

Data transmission in the computer represents the direction of the flow of the output to the devices communicating. Because of this, it is also named directional mode and data communication. Data transmission can be divided into three types, or there are three types of data transmission.

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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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Domain-driven data architecture

Martin Fowler

Zhamak explains the first part of the data mesh concept - using the ideas behind Domain-Driven Design to structure the data platform. more…. skip-home-page

The Big Payoff of Application Analytics

Outdated or absent analytics won’t cut it in today's data-driven applications. And they won’t cut it for your end users, your development team, or your business. Learn how 5 companies used embedded analytics to achieve huge returns and greater value than anticipated.

Data Types

DevOps.com

The post Data Types appeared first on DevOps.com. Blogs ROELBOB Build data types deployment humor parody programming satire

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Harnessing the Value of Log Data Analytics

DevOps.com

Each log is a file whose data describes an event such as a user action, service request, application task or compute error. The post Harnessing the Value of Log Data Analytics appeared first on DevOps.com.

Self-serve data platform

Martin Fowler

One of the main concerns of distributing the ownership of data to the domains is the duplicated effort and skills required to operate the data pipelines technology stack and infrastructure in each domain. Luckily, building common infrastructure as a platform is a well understood and solved problem; though admittedly the tooling and techniques are not as mature in the data ecosystem.

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Connecting the Data Lifecycle

Cloudera

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . You can become a data hero too.

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The Rise of Embedded Self-Service Analytics

Speaker: Chris Von Simson & Nat Venkataraman

Can your users get the data and analytics they need without leaving your application? Watch this webinar with Chris von Simson of Dresner Advisory Services as he shares why user enablement has emerged as the theme in today’s embedded analytics landscape.