Data Engineering Podcast

JUNE 4, 2023

DataOps has arisen as a parallel set of practices to that of DevOps teams as a means of reducing wasted effort. Agile Data Engine is a platform designed to handle the infrastructure side of the DataOps equation, as well as providing the insights that you need to manage the human side of the workflow.

Data Engineering 130

Data Engineering Data Engineer Engineering Data Lake 130

Monte Carlo

MARCH 28, 2024

Enter the nascent discipline of DataOps. Similar to how DevOps applies CI/CD to software development and operations, DataOps entails a CI/CD-like, automation-first approach to building and scaling data products. Table of Contents What Is The Difference Between DataOps and DevOps? What is the Salary of DataOps vs. DevOps?

Data Pipeline 52

Data Pipeline Coding Machine Learning Data Warehouse 52

Christophe Blefari

JANUARY 14, 2024

The details: it's a 27-hour course called DataOps. I'm very happy with this new DataOps lecture because it's much closer to what's really going on in the data world. It's always very exciting to go back and teach students, to help them discover the world of data from another perspective.

Google Cloud 130

Google Cloud Data SQL Python 130

Jesse Anderson

MAY 9, 2023

To better understand what people meant by their homegrown methodology, I contacted people to get more information. It seems like the ideas for the major methodologies get adopted in pieces (either what fits or what pieces a manager latches on to) but not fully implemented.

Software Engineer 147

Software Engineer Software Engineering Consulting Data 147

Christophe Blefari

FEBRUARY 18, 2023

When the Data News lands on Saturday ( credits ) In last week newsletter I've also share what is a metrics store, which led to a longer edition than usual and I saw that a few people did not like it this way. Still, what is a metrics store ? Is DataOps really a thing? This is why DataOps is important.

Software Engineer 100

Software Engineer Software Engineering Data Validation Data 100

Data Engineering Podcast

FEBRUARY 5, 2023

What do you have planned for the future of the podcast? Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Summary This podcast started almost exactly six years ago, and the technology landscape was much different than it is now.

Data Engineering 147

Data Engineering Data Engineer Engineering PostgreSQL 147

Data Engineering Podcast

MAY 3, 2021

Taking cues from the DevOps movement of the past decade data professionals are orienting around the concept of DataOps. More than just a collection of tools, there are a number of organizational and conceptual changes that a proper DataOps approach depends on. RudderStack’s smart customer data pipeline is warehouse-first.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

François Nguyen

JANUARY 29, 2021

The agile part of DataOps In this previous article, we have defined dataops as a”combination of tools and methods inspired by Agile, Devops and Lean Manufacturing » (thanks to DataKitchen for this definition). “Data is like a box of chocolates, you never know what you’re gonna get.”

Manufacturing 130

Manufacturing Data Analysis Data Building 130

François Nguyen

JANUARY 18, 2021

To finish the trilogy (Dataops, MLops), let’s talk about DataGovOps or how you can support your Data Governance initiative. The Dataops Heritage In my previous article, I have described the loop around the devops part of dataops. You should visit their website , you will find incredible good stuff there.

Data Governance 130

Data Governance Metadata Government Data Pipeline 130

DataKitchen

DECEMBER 13, 2021

Before we shut the door on 2021, we would like to share our most popular DataOps content in hopes that it can help you as you learn about and implement DataOps. We hope you and your family have happy holidays and we look forward to continuing your DataOps journey with you in the new year. The DataOps Vendor Landscape, 2021.

Data Governance 98

Data Governance Data Architecture Government Data Engineering 98

Christophe Blefari

JANUARY 26, 2024

Next week, I'll be wrapping up my DataOps lecture by incorporating how to deploy machine learning models. So define—as a metric—what you don't want to have. Inputs — This is what you ask from the users to feed your algorithm. Hey ( credits ) Hey, new week new email.

Google Cloud 130

Google Cloud Algorithm Data Java 130

Databand.ai

AUGUST 30, 2023

DataOps Architecture: 5 Key Components and How to Get Started Ryan Yackel August 30, 2023 What Is DataOps Architecture? DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

DataKitchen

JULY 3, 2023

Data Journey First DataOps Putting Problems in Your Data Estate at the Forefront Welcome to the high-octane world of DataOps, a powerhouse that turbocharges data analytics development and management. Historically, automation has taken center stage in the theater of DataOps. Data Teams Already Have A Ton of Things To Get Done.

Data Validation 52

Data Validation Data Data Analytics Architecture 52

DataKitchen

MARCH 12, 2024

Reducing the errors your customers find and those they do not are key success metrics of Data Observability Using DataKitchen DataOps Observability and DataOps TestGen. DataKitchen Customer Quotes “After implementing, we reduced errors to just about one per quarter. Tests assess important questions, such as “Is the data correct?”

Pharmaceutical 48

Pharmaceutical Data Datasets Data Analytics 48

DataKitchen

JANUARY 3, 2022

Instead of throwing people and budgets at problems, DataOps offers a way to utilize automation to systematize analytics workflows. DataOps consolidates processes and workflows into a process hub that curates and manages the workflows that drive the creation of analytics. In business analytics, fire-fighting and stress are common.

Business Analyst 98

Business Analyst Data Lake Consulting Data Analytics 98

Data Engineering Podcast

APRIL 16, 2022

In this episode Demetrios Brinkmann and David Aponte share their perspectives on this rapidly changing space and what they have learned from their work building the MLOps community through blog posts, podcasts, and discussion forums. Can you describe what MLOps is? How does it relate to DataOps? is it just another buzzword?)

Data Engineering 100

Data Engineering Data Engineer Engineering IT 100

Databand.ai

JULY 17, 2023

DataOps vs. MLOps: Similarities, Differences, and How to Choose Joseph Arnold July 17, 2023 What Is DataOps? DataOps , short for Data Operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data management processes.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

DataKitchen

AUGUST 24, 2023

Since the first edition of the DataOps Cookbook in 2019, we have talked with thousands of companies about their struggles to deliver data-driven insight to their customers. And on top of that, they are all unhappy, stressed, and wondering what went wrong. In many ways, they all have the same problems.

Data Analytics 52

Data Analytics Systems Process Building 52

Christophe Blefari

MAY 18, 2023

As I often do I've overlooked the 70 presentations and here a medley of what I've liked. You should answer 4 questions: what happened, why did it happened, what's going to happen, what should we do next. " Since joining Google, he's been working on Malloy, a new way to query data.

Data 130

Data BI Consulting Data Science 130

Databand.ai

AUGUST 30, 2023

DataOps Framework: 4 Key Components and How to Implement Them Eric Jones August 30, 2023 What Is a DataOps Framework? The DataOps framework is a set of practices, processes, and technologies that enables organizations to improve the speed, accuracy, and reliability of their data management and analytics operations.

Data Governance 52

Data Governance Data Pipeline Government Data Cleanse 52

Databand.ai

AUGUST 30, 2023

DataOps Tools: Key Capabilities & 5 Tools You Must Know About Ryan Yackel August 30, 2023 What Are DataOps Tools? DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Data Engineering Podcast

AUGUST 25, 2021

In order to make this world of DataOps more accessible and manageable the team at Nexla has built a platform that decouples the logical unit of data from the underlying mechanisms so that you can focus on the problems that really matter to your business. Then what do you do? Can you describe what Nexla is and the story behind it?

Data 100

Data Metadata Data Engineering Data Engineer 100

DataKitchen

NOVEMBER 4, 2021

DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. The requirement to integrate enormous quantities and varieties of data coupled with extreme pressure on analytics cycle time has driven the pharmaceutical industry to lead in DataOps adoption. The Last Mile Problem.

Process 98

Process Data Process Pharmaceutical Data Lake 98

The Modern Data Company

JANUARY 22, 2024

The result—no matter the final configuration or what a company’s data landscape looks like—is a data ecosystem characterized by consistency, reliability, and absolute adherence to governance principles. Let’s talk about it. Operational data integration leadership DataOS supports a broad spectrum of use cases.

Data Integration 98

Data Integration Metadata Government Unstructured Data 98

Data Engineering Podcast

APRIL 27, 2020

Summary Data is a critical element to every role in an organization, which is also what makes managing it so challenging. With so many different opinions about which pieces of information are most important, how it needs to be accessed, and what to do with it, many data projects are doomed to failure.

Hadoop 100

Hadoop Data Workflow Data Engineering Data Engineer 100

DataKitchen

AUGUST 9, 2021

Below is our third post (3 of 5) on combining data mesh with DataOps to foster greater innovation while addressing the challenges of a decentralized architecture. We’ve talked about data mesh in organizational terms (see our first post, “ What is a Data Mesh? ”) and how team structure supports agility. DataOps Meta-Orchestration.

Pharmaceutical 98

Pharmaceutical Raw Data Data Lake Data 98

DataKitchen

JULY 12, 2023

While people can do what they want with language (and many often do), syntax helps ordinary language users understand how to organize words to make the most sense. What is a meaningful test for your business? What is the acceptable rate of change? In linguistics, Syntax is the study of sentence structure and grammar rules.

Pharmaceutical 52

Pharmaceutical Manufacturing Finance Data Engineering 52

DataKitchen

FEBRUARY 1, 2021

Every DataOps initiative starts with a pilot project. DataOps addresses a broad set of use cases because it applies workflow process automation to the end-to-end data-analytics lifecycle. DataOps reduces errors, shortens cycle time, eliminates unplanned work, increases innovation, improves teamwork, and more.

Project 98

Project Raw Data Consulting Data Science 98

DataKitchen

APRIL 28, 2021

Forrester relates that out of 25,000 reports published by the firm last year, the report on data fabrics and DataOps ranked in the top ten for downloads in 2020. What is a Data Fabric? Gartner included data fabrics in their top ten trends for data and analytics in 2019. This is happening to the term “data fabric.”

Data Pipeline 98

Data Pipeline Data Data Analytics Architecture 98

DataKitchen

JANUARY 20, 2021

As DataOps activity takes root within an enterprise, managers face the question of whether to build centralized or decentralized DataOps capabilities. The beauty of DataOps is that you don’t have to choose between centralization and freedom. DataOps Technical Services. DataOps Center of Excellence. DataOps Dojo .

Education 97

Education Coding Project Engineering 97

DataKitchen

SEPTEMBER 20, 2021

Data organizations don’t always have the budget or schedule required for DataOps when conceived as a top-to-bottom, enterprise-wide transformational change. An essential part of the DataOps methodology is Agile Development , which breaks development into incremental steps. In short, Lean DataOps is the fastest path to DataOps value.

Data Pipeline 98

Data Pipeline Data Cleanse Process Architecture 98

The Modern Data Company

JANUARY 22, 2024

Let’s talk about it. The Modern Story: Navigating Complexity and Rethinking Data in The Business Landscape Enterprises face a data landscape marked by the proliferation of IoT-generated data, an influx of unstructured data, and a pervasive need for comprehensive data analytics.

Data Integration 87

Data Integration Metadata Government Unstructured Data 87

DataKitchen

DECEMBER 6, 2022

We are excited that Gartner released its ‘Market Guide to DataOps’ ! The document they wrote is exceptionally close to what we see in the market and what our products do ! This document is essential because buyers look to Gartner for advice on what to do and how to buy IT software. What is missing?

Data Lake 52

Data Lake Hadoop Government Data Analytics 52

Monte Carlo

APRIL 26, 2022

What is DataOps? DataOps is a discipline that merges data engineering and data science teams to support an organization’s data needs, in a similar way to how DevOps helped scale software engineering. In this guide, we’ll explain each of the following: What is DataOps?

IT 64

IT Data Pipeline Data Engineering Data Engineer 64

DataKitchen

FEBRUARY 21, 2023

What is Gartner’s advice for a new data engineering lead like Marcus? Adopt DataOps Practices : “Successful data engineering teams are cross-functional and adopt DataOps practices.” Data team morale is consistent with DataKitchen’s own research. It’s not been going well. A better ETL tool? Pick some other hot tool?

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Data Engineering Podcast

SEPTEMBER 25, 2021

That leaves DataOps reactive to data quality issues and can make your consumers lose confidence in your data. What does the term "Data Reliability Engineering" mean? What does the term "Data Reliability Engineering" mean? What is encompassed under the umbrella of Data Reliability Engineering?

Engineering 100

Engineering Metadata Data Data Engineering 100

DataKitchen

JANUARY 6, 2021

As data professionals, we know the value and impact of DataOps: streamlining analytics workflows, reducing errors, and improving data operations transparency. Being able to quantify the value and impact helps leadership understand the return on past investments and supports alignment with future enterprise DataOps transformation initiatives.

Pharmaceutical 98

Pharmaceutical Consulting Utilities Programming 98