DataKitchen

DECEMBER 29, 2022

The Terms and Conditions of a Data Contract are Automated Production Data Tests. A data contract is a formal agreement between two parties that defines the structure and format of data that will be exchanged between them. The best data contract is an automated production data test.

Testing 130

Testing Statistics Data Quality Data Integration 130

Smart Data Collective

APRIL 20, 2022

It takes a lot of split-testing and data collection to optimize your strategy to approach these types of conversion rates. Companies with an in-depth understanding of data analytics will have more successful Amazon PPC marketing strategies. However, it is important to make sure the data is reliable.

Data Quality 117

Data Quality Analytics Testing Sales 117

AWS Big Data

JUNE 6, 2023

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. An AWS Glue crawler crawls the results.

Data Quality 68

Data Quality Metrics Visualization Dashboards 68

DataKitchen

MAY 7, 2024

DataKitchen Training And Certification Offerings For Individual contributors with a background in Data Analytics/Science/Engineering Overall Ideas and Principles of DataOps DataOps Cookbook (200 page book over 30,000 readers, free): DataOps Certificatio n (3 hours, online, free, signup online): DataOps Manifesto (over 30,000 signatures) One (..)

Data Quality 167

Data Quality Testing Consulting Metrics 167

AWS Big Data

OCTOBER 10, 2023

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

Data Quality 87

Data Quality Data Governance Data Lake Testing 87

Ontotext

NOVEMBER 16, 2023

In the first part of this series of technological posts, we talked about what SHACL is and how you can set up validation for your data. Tacking the data quality issue — bit by bit or incrementally There are two main approaches to validating your data, which would be dependent on the specific implementation.

Data Quality 69

Data Quality Reporting Testing Technology 69

CIO Business Intelligence

AUGUST 2, 2022

We are also combining that with data from different sources as a pilot to see if it makes sense and tests out a hypothesis. The second is the data quality in our legacy systems. So, data quality is definitely one of our biggest challenges that is tied closely to the foundational changes. That’s one.

Data Quality 97

Data Quality Digital Transformation Machine Learning Predictive Analytics 97

DataKitchen

MAY 10, 2024

The Third of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Testing 100

Testing Metrics Data Quality Dashboards 100

DataKitchen

MAY 10, 2024

The Second of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Data Quality 100

Data Quality Testing Software Dashboards 100

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Fast, Safe Development and Deployment (#4) Introduction The integrity and functionality of new code, tools, and configurations during the development and deployment stages are crucial. This process is critical as it ensures data quality from the onset. How Many Tests Ran Per Day?

Testing 100

Testing Cost-Benefit Data Quality Dashboards 100

Octopai

JULY 11, 2022

And when business users don’t complain, but you know the data isn’t good enough to make these types of calls wisely, that’s an even bigger problem. How are you, as a data quality evangelist (if you’re reading this post, that must describe you at least somewhat, right?), Tie data quality directly to business objectives.

Data Quality 79

Data Quality Strategy Business Objectives Sales 79

Alation

DECEMBER 7, 2021

Alation and Soda are excited to announce a new partnership, which will bring powerful data-quality capabilities into the data catalog. Soda’s data observability platform empowers data teams to discover and collaboratively resolve data issues quickly. Does the quality of this dataset meet user expectations?

Data Quality 52

Data Quality Metadata Testing Data Governance 52

TDAN

MARCH 16, 2021

The purpose of this article is to provide a model to conduct a self-assessment of your organization’s data environment when preparing to build your Data Governance program. Take the […].

Data Governance 105

Data Governance Testing Modeling Data Quality 105

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. We kept adding tests over time; it has been several years since we’ve had any major glitches. Tests assess important questions, such as “Is the data correct?”

Metrics 120

Metrics Software Cost-Benefit Testing 120

Jim Harris

JANUARY 1, 2018

The Chicken Littles of Data Quality use sound bites like “data quality problems cost businesses more than $600 billion a year!” or “poor data quality costs organizations 35% of their revenue!” Furthermore, the reason that citing specific examples of poor data quality (e.g.,

Data Quality 77

Data Quality Cost-Benefit Consulting Dashboards 77

DataKitchen

NOVEMBER 10, 2023

Extrinsic Control Deficit: Many of these changes stem from tools and processes beyond the immediate control of the data team. Unregulated ETL/ELT Processes: The absence of stringent data quality tests in ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes further exacerbates the problem.

Data Quality 141

Data Quality Testing Data Lake Data Integration 141

Analytics Vidhya

MARCH 13, 2024

Introduction Whether you’re a fresher or an experienced professional in the Data industry, did you know that ML models can experience up to a 20% performance drop in their first year? Monitoring these models is crucial, yet it poses challenges such as data changes, concept alterations, and data quality issues.

Data Quality 282

Data Quality Modeling Analytics IT 282

Octopai

OCTOBER 26, 2022

DataOps is an approach to best practices for data management that increases the quantity of data analytics products a data team can develop and deploy in a given time while drastically improving the level of data quality. SPC is the continuous testing of the results of automated manufacturing processes.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

DataKitchen

MAY 10, 2024

Data Evaluation Before new data sets are introduced into production environments, they must be thoroughly evaluated and cleaned. This initial stage of data observability ensures that data quality is maintained from the start, preventing errors that could affect downstream processes and decisions.

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Data Quality Dashboards Strategy Testing 146

DataKitchen

FEBRUARY 27, 2024

However, the foundation of their success rests not just on sophisticated algorithms or computational power but on the quality and integrity of the data they are trained on and interact with. The Imperative of Data Quality Validation Testing Data quality validation testing is not just a best practice; it’s imperative.

Data Quality 120

Data Quality Unstructured Data Testing Modeling 120

DataKitchen

FEBRUARY 23, 2024

Webinar: Beyond Data Observability: Personalization DataKitchen DataOps Observability Problem Statement White Paper: ‘Taming Chaos’ Technical Product Overview Four-minute online demo Detailed Product: Documentation Webinar: Data Observability Demo Day DataKitchen DataOps TestGen Problem Statement White Paper: ‘Mystery Box Full Of Data Errors’ (..)

Testing 120

Testing Data-driven Metrics Data Quality 120

DataKitchen

JUNE 19, 2023

DataOps TestGen delivers simple, fast data quality test generation and execution. DataOps TestGen profiles your data and algorithmically generates dozens of data validations. Your Data Journey starts with verifying that you can trust your data and re-verifying it every time you refresh it in production.

Data Quality 130

Data Quality Testing IT 130

DataKitchen

MARCH 5, 2024

Stakeholders, from internal teams to external clients, seek confidence in the data they use and depend on. This confidence can only be built through transparency, proactive error detection, and a robust data quality and observability framework. It’s just a matter of time.

Data Quality 150

Data Quality Measurement Testing Data-driven 150

Ontotext

MAY 26, 2021

In the above case of merging information about companies from different data sources, data linking helps us encode the real-world business logic into data linking rules. But, before we can have any larger scale implementation of these rules, we have to test their validity. How does the Gold Standard help data linking?

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

DataKitchen

JANUARY 25, 2022

Ensuring that data is available, secure, correct, and fit for purpose is neither simple nor cheap. Companies end up paying outside consultants enormous fees while still having to suffer the effects of poor data quality and lengthy cycle time. . When a job is automated, there is little advantage to outsourcing. .

Consulting 244

Consulting Testing Data Lake Data Quality 244

DataKitchen

JUNE 19, 2023

Another way to look at the five pillars is to see them in the context of a typical complex data estate. .” – Take A Bow, Rihanna (I may have heard it wrong) Validating data quality at rest is critica l to the overall success of any Data Journey. The image above shows an example ‘’data at rest’ test result.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

DataKitchen

OCTOBER 2, 2023

.’ What’s a Data Journey? Data Journeys track and monitor all levels of the data stack, from data to tools to code to tests across all critical dimensions. A Data Journey supplies real-time statuses and alerts on start times, processing durations, test results, and infrastructure events, among other metrics.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

Rocket-Powered Data Science

FEBRUARY 15, 2023

Clean it, annotate it, catalog it, and bring it into the data family (connect the dots and see what happens). Keep it agile, with short design, develop, test, release, and feedback cycles: keep it lean, and build on incremental changes. Test early and often. Test and refine the chatbot. Expect continuous improvement.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

DataKitchen

NOVEMBER 18, 2022

As he thinks through the various journeys that data take in his company, Jason sees that his dashboard idea would require extracting or testing for events along the way. 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. Data and tool tests.

Testing 130

Testing Statistics Measurement Metrics 130

DataKitchen

JUNE 7, 2021

Improve Collaboration, both Inter- and Intra -team – If the individuals in your data-analytics team don’t work together, it can impact analytics-cycle time, data quality, governance, security and more. A data arrival report enables you to track data suppliers and quickly spot delivery issues. Lower Error Rates.

Testing 130

Testing IT Measurement Data-driven 130

Smart Data Collective

AUGUST 11, 2022

How Artificial Intelligence is Impacting Data Quality. Artificial intelligence has the potential to combat human error by taking up the tasking responsibilities associated with the analysis, drilling, and dissection of large volumes of data. Data quality is crucial in the age of artificial intelligence.

Data Quality 130

Data Quality Machine Learning Digital Transformation Big Data 130

CIO Business Intelligence

MARCH 18, 2024

Laying the foundation To develop POC implementations, Menon and her team are establishing a lab that is expected to debut in March 2024 for testing AI tools before rollout. The lab, housed in a county office building, will pull members from multiple departments, including the county’s data team and architecture team.

Risk 133

Risk Cost-Benefit Data Processing Testing 133

DataKitchen

JANUARY 19, 2022

Imagine a large enterprise yielding significant value from their Matillion-Snowflake integration, but wishing to expand the scope of data pipeline deployment, testing, and monitoring. DataKitchen triggers a Matillion job, then retrieves execution parameters that can be used in DataKitchen tests.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

Smarten

JANUARY 30, 2024

The right self-serve data prep solution can provide easy-to-use yet sophisticated data prep tools that are suitable for your business users, and enable data preparation techniques like: Connect and Mash Up Auto Suggesting Relationships JOINS and Types Sampling and Outliers Exploration, Cleaning, Shaping Reducing and Combining Data Insights (Data Quality (..)

Analytics 67

Analytics Data Quality Visualization Metadata 67

DataKitchen

OCTOBER 20, 2023

Deploying a Data Journey Instance unique to each customer’s payload is vital to fill this gap. Such an instance answers the critical question of ‘Dude, Where is my data?’ ’ while maintaining operational efficiency and ensuring data quality—thus preserving customer satisfaction and the team’s credibility.

Insurance 176

Insurance Metadata Data-driven Data Quality 176

CIO Business Intelligence

MAY 8, 2024

So depending on where the data comes from, it can be terrible or very easy and can take half an hour if you’re lucky, or the whole day if you’re not. After getting all the data under control, we needed to test it by loading it into a test environment and give it to our register operations team to validate if it all looked correct.

Risk 111

Risk Testing Strategy Technology 111

DataKitchen

APRIL 11, 2023

The conversation then moved to the importance of logistics and data quality in analytics, particularly in the pharmaceutical industry. James highlighted the need for a reliable data chain to ensure the end analyst can focus on delivering value. Testing, according to James, is crucial in data analysis.

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Data Analytics Analytics Cost-Benefit Data Quality 130