IBM Big Data Hub

DECEMBER 18, 2019

Enter DataOps. Data volume and data types continue to grow, as do the different types of data citizens—ranging from business users to data scientists. As a result, data management and delivery often become critical bottlenecks.

Management 75

Management IT 75

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?

Software 130

Software Marketing Data Lake Testing 130

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.

Business Objectives 245

Business Objectives Cost-Benefit Measurement Metrics 245

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 Analytics 245

Business Analytics Analytics Testing Dashboards 245

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 .

Metrics 243

Metrics Experimentation Measurement Testing 243

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.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

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.”

Statistics 246

Statistics Optimization Technology Data Analytics 246

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.

Data Quality 130

Data Quality Testing Manufacturing Finance 130

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.

Testing 246

Testing Data Lake Metadata Publishing 246

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.

Testing 246

Testing Metrics Measurement Dashboards 246

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?”

Metrics 120

Metrics Software Cost-Benefit Testing 120

DataKitchen

DECEMBER 9, 2022

Query> DataOps. ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

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.

Cost-Benefit 246

Cost-Benefit Testing Strategy Consulting 246

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-driven 130

Data-driven Testing Risk Cost-Benefit 130

DataKitchen

NOVEMBER 18, 2022

This is the third post in DataKitchen’s four-part series on DataOps Observability. So, the only way for a data journey to truly observe what’s happening is to get his tools and pipelines to auto-report events. Part 3: Considering the Elements of Data Journeys. Observability includes the following components.

Testing 130

Testing Statistics Measurement Metrics 130

DataKitchen

DECEMBER 9, 2022

DataKitchen, the leading provider of DataOps solutions, has been named a Representative and “super cool, way out there, OP, world best” DataOps vendor in the December 2022 Gartner® Market Guide for DataOps Tools. What gives?” December 08, 2022, 08:00 ET | Source: DataKitchen.

Reporting 130

Reporting Marketing Software Testing 130

DataKitchen

DECEMBER 1, 2022

Well, don’t worry because DataOps is here to help! In this post, we’ll discuss how DataOps Observability and Automation can relieve team stress and show you how to get started. All of those things can be enabled by DataOps. With DataOps, data teams can ship data analytics systems faster and more confidently.

Experimentation 130

Experimentation Data-driven Risk Optimization 130

DataKitchen

AUGUST 19, 2021

Below is our fourth post (4 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a decentralized architecture. Figure 3: Example DataOps architecture based on the DataKitchen Platform. The data scientists and analysts have what they need to build analytics for the user.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

DataKitchen

NOVEMBER 28, 2022

This is the final post in DataKitchen’s four-part series on DataOps Observability. DataOps Observability Benefits Summary. Jason formed a small team and implemented DataKitchen DataOps Observability. DataOps Observability provides critical features and benefits. Part 4: Reviewing the Benefits.

Testing 130

Testing Reporting Dashboards Visualization 130

DataKitchen

MAY 10, 2021

After establishing a solid strategy, the second phase involves planning key processes and practices to support the strategy, including “the emerging and increasingly important DataOps and ModelOps processes and methodologies.”. Blog: What is DataOps ? White Paper: DataOps is Not Just DevOps for Data .

Data-driven 130

Data-driven Data Architecture Machine Learning Strategy 130

DataKitchen

OCTOBER 27, 2022

. Question: What is something the data industry is missing? I think it’s observability-led DataOps. The first step in solving that pain is to observe what’s happening with your data and analytics ‘estate’ and stick little thermometers at various points in the process and measure. Is it late?

Dashboards 130

Dashboards Measurement Testing Modeling 130

DataKitchen

JUNE 12, 2023

About seven years ago, we wrote the DataOps Manifesto. We wrote the first version because, after talking with hundreds of people at the 2016 Strata Hadoop World Conference, very few easily understood what we discussed at our booth and conference session. So why another manifesto in the world? Why should I care?

Testing 130

Testing Data Lake Dashboards Data Science 130

DataKitchen

NOVEMBER 10, 2023

Adopt an iterative approach, characteristic of DataOps and Agile methodologies, to continuously improve data processes and systems. Solutions to Reign in the Chaos Implementing Data Observability Platforms: Tools like DataKitchen’s DataOps Observability provide an overarching view of the entire Data Journey.

Data Quality 141

Data Quality Testing Data Lake Data Integration 141

DataKitchen

JUNE 7, 2021

The primary source of information about DataOps is from vendors (like DataKitchen) who sell enterprise software into the fast-growing DataOps market. There are over 70 vendors that would be happy to assist in your DataOps initiative. What can you do? DataOps is not an all-or-nothing proposition.

Testing 130

Testing IT Measurement Data-driven 130

DataKitchen

DECEMBER 20, 2020

The Role of DataOps and the DataOps Engineer. Within the data industry, this effort is called DataOps , and it is implemented by someone called a DataOps Engineer. If you want to attain greater business agility through faster, more responsive data analytics, then the DataOps Engineer should be your first hire.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

DataKitchen

MARCH 11, 2021

Gartner identified XOps (DataOps, ModelOps, DevOps) as one of the top trends in data and analytics for 2021. What is XOps? . DataKitchen White Paper: DataOps is NOT Just DevOps for Data. DataKitchen Blog: Improving Teamwork in Data Analytics with DataOps. Opportunity. Implementation.

Analytics 130

Analytics Machine Learning Modeling Reporting 130

DataKitchen

JUNE 30, 2021

Joe Reis, host of the Data Nerd Herd podcast & Ternary Data CEO & Co-Founder, interviews DataKitchen CEO Chris Bergh about what DataOps is & why it matters. The post DataOps with Chris Bergh first appeared on DataKitchen.

Data Processing 130

Data Processing IT 130

DataKitchen

JANUARY 5, 2021

The disparate toolchains illustrate how each group resides in its own segregated silo without an ability to easily understand what other groups are doing. In the data analytics market, this endeavor is called DataOps. Data Governance/Catalog (Metadata management) Workflow – Alation, Collibra, Wikis.

Testing 147

Testing Data Governance Metadata Visualization 147

DataKitchen

JANUARY 25, 2021

What happened? DataOps uses automation to create unprecedented visibility into data operations. Below we’ll show an actual report used by a DataOps enterprise. It helps people keep their “finger on the pulse” of what is happening, so stakeholders started calling it the “Pulse Report.”. The Pulse Report.

Reporting 243

Reporting Testing Enterprise Analytics 243

DataKitchen

OCTOBER 28, 2021

What Is AI Bias? Addressing AI Bias With DataOps. The data industry employs a new term, “ DataOps ,” when describing the application of manufacturing quality methods like lean manufacturing and Six Sigma to data and analytics. Let’s discuss how DataOps can address AI bias. That’s an important start.

Testing 130

Testing IT Manufacturing Metrics 130

DataKitchen

MARCH 16, 2023

What should be in that report about your data team? What should I track? What are the metrics that matter? Gartner attempted to list every metric under the sun in their recent report , “T oolkit: Delivery Metrics for DataOps, Self-Service Analytics, ModelOps, and MLOps, ” published February 7, 2023. Introduction.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

DataKitchen

MARCH 5, 2024

It’s tempting to adopt the “ What, me worry? Implementing rigorous DataOps Observability practices, including automated testing, observability tools, and a culture of continuous improvement, can transform how your team addresses data reliability and accuracy. ” attitude under these seemingly calm conditions.

Data Quality 150

Data Quality Measurement Testing Data-driven 150

DataKitchen

JUNE 19, 2023

Our recent survey showed that 97% of data engineers report experiencing burnout in their day-to-day jobs. Perhaps we could just chill out in those stressful situations and “let go,” as the Buddha suggests. Given the complicated distributed systems we use to get value from data and the diversity of data, we need a simplifying framework.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

Octopai

OCTOBER 26, 2022

Enter DataOps. How can DataOps help here? The goal of DataOps methodology is to enable Data to drive Op eration s : to have a direct, constructive impact on the business operations of the company. DataOps realizes that the purpose of having data is to use the data. So what is DataOps ? And it should be.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

DataKitchen

JANUARY 18, 2023

That’s why a key goal of DataOps is to expose your best-laid plans to real-life urgencies faster and initiate that crucial feedback loop sooner. With DataOps, you define a framework and a set of best practices to deal with real-world changes and crises. The real world is a bit more pungent. Testing is intrinsic to the job. .

Testing 130

Testing Data-driven Risk Strategy 130

CIO Business Intelligence

DECEMBER 22, 2022

What is DataOps? DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. DataOps goals According to Dataversity , the goal of DataOps is to streamline the design, development, and maintenance of applications based on data and data analytics.

Analytics 130

Analytics Machine Learning Software Data Quality 130

DataRobot Blog

AUGUST 16, 2022

What are companies actually doing today? The survey asked companies how they used two overlapping types of tools to deploy analytical models: Data operations (DataOps) tools, which focus on creating a manageable, maintainable, automated flow of quality-assured data. Survey Questions. Improving Success. Realistic Expectations.

Digital Transformation 52

Digital Transformation ROI Testing Modeling 52