Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is. What is data integrity?

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

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

AWS Big Data

SEPTEMBER 4, 2024

Effective data analytics relies on seamlessly integrating data from disparate systems through identifying, gathering, cleansing, and combining relevant data into a unified format. Reverse ETL use cases are also supported, allowing you to write data back to Salesforce. Kamen Sharlandjiev is a Sr. His secret weapon?

Data Integration 107

Data Integration Data Lake Data-driven Cost-Benefit 107

Sisense

SEPTEMBER 23, 2019

Mike Cohn’s famous Test Pyramid places API tests at the service level (integration), which suggests that around 20% or more of all of our tests should focus on APIs (the exact percentage is less important and varies based on our needs). So the importance of API testing is obvious. API test actions.

Testing 89

Testing Strategy Modeling Publishing 89

DataKitchen

JANUARY 25, 2022

DataOps improves the robustness, transparency and efficiency of data workflows through automation. For example, DataOps can be used to automate data integration. Previously, the consulting team had been using a patchwork of ETL to consolidate data from disparate sources into a data lake.

Consulting 244

Consulting Testing Data Quality Data Lake 244

AWS Big Data

JULY 26, 2023

Many AWS customers have integrated their data across multiple data sources using AWS Glue , a serverless data integration service, in order to make data-driven business decisions. Are there recommended approaches to provisioning components for data integration?

Data Integration 95

Data Integration Snapshot Testing Visualization 95

Octopai

AUGUST 3, 2022

It’s also a critical trait for the data assets of your dreams. What is data with integrity? Data integrity is the extent to which you can rely on a given set of data for use in decision-making. Where can data integrity fall short? Too much or too little access to data systems.

Data Integration 98

Data Integration Manufacturing Data Quality Data Governance 98

David Menninger's Analyst Perspectives

NOVEMBER 19, 2024

To improve data reliability, enterprises were largely dependent on data-quality tools that required manual effort by data engineers, data architects, data scientists and data analysts.

Data Quality 130

Data Quality Dashboards Data-driven Software 130

AWS Big Data

JANUARY 9, 2025

Simplified data corrections and updates Iceberg enhances data management for quants in capital markets through its robust insert, delete, and update capabilities. These features allow efficient data corrections, gap-filling in time series, and historical data updates without disrupting ongoing analyses or compromising data integrity.

Metadata 111

Metadata Snapshot Cost-Benefit Optimization 111

DataKitchen

MAY 10, 2021

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. Tie tests to alerts.

Testing 214

Testing Manufacturing Data Quality Statistics 214

O'Reilly on Data

OCTOBER 11, 2022

Selenium , the first tool for automated browser testing (2004), could be programmed to find fields on a web page, click on them or insert text, click “submit,” scrape the resulting web page, and collect results. But the core of the process is simple, and hasn’t changed much since the early days of web testing. What’s required?

Data Integration 330

Data Integration Insurance Dashboards Data-driven 330

CIO Business Intelligence

FEBRUARY 26, 2025

The problem is that, before AI agents can be integrated into a companys infrastructure, that infrastructure must be brought up to modern standards. In addition, because they require access to multiple data sources, there are data integration hurdles and added complexities of ensuring security and compliance.

IT 141

IT Enterprise Interactive Data Quality 141

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors.

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

AWS Big Data

DECEMBER 16, 2024

For each service, you need to learn the supported authorization and authentication methods, data access APIs, and framework to onboard and test data sources. This approach simplifies your data journey and helps you meet your security requirements.

Visualization 89

Visualization Data Processing Testing Publishing 89

Business Over Broadway

SEPTEMBER 27, 2018

genetic counseling, genetic testing). Data Integration as your Customer Genome Project. Data Integration is an exercise in creating your customer genome. Using the 2×2 graphical approach to understanding data size (i.e., pharmacogenomics) and risk assessment of genetic disorders (e.g.,

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

DataKitchen

JANUARY 19, 2022

The Matillion data integration and transformation platform enables enterprises to perform advanced analytics and business intelligence using cross-cloud platform-as-a-service offerings such as Snowflake. DataKitchen acts as a process hub that unifies tools and pipelines across teams, tools and data centers.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

DataKitchen

NOVEMBER 18, 2021

Write tests that catch data errors. Build observability and transparency into your end-to-end data pipelines. We talk about systemic change, and it certainly helps to have the support of management, but data engineers should not underestimate the power of the keyboard. Automate manual processes. Implement DataOps methods.

Testing 246

Testing Data Governance Measurement Software 246

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 139

Data Quality Testing Data Lake Data Integration 139

DataKitchen

NOVEMBER 18, 2022

Question: What is the difference between Data Quality and Observability in DataOps? Data Quality is static. It is the measure of data sets at any point in time. A financial analogy: Data Quality is your Balance Sheet, Data Observability is your Cash Flow Statement.

Data Quality 130

Data Quality Testing Measurement Data Integration 130

AWS Big Data

OCTOBER 11, 2024

It covers the essential steps for taking snapshots of your data, implementing safe transfer across different AWS Regions and accounts, and restoring them in a new domain. This guide is designed to help you maintain data integrity and continuity while navigating complex multi-Region and multi-account environments in OpenSearch Service.

Snapshot 110

Snapshot Dashboards Management Testing 110

O'Reilly on Data

DECEMBER 12, 2019

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. It’s a very simple and powerful idea: simulate data that you find interesting and see what a model predicts for that data. 6] See: Testing and Debugging Machine Learning Models. [7]

Machine Learning 226

Machine Learning Modeling Testing Risk Management 226

AWS Big Data

NOVEMBER 22, 2024

Testing these upgrades involves running the application and addressing issues as they arise. Each test run may reveal new problems, resulting in multiple iterations of changes. They then need to modify their Spark scripts and configurations, updating features, connectors, and library dependencies as needed. Python 3.7) to Spark 3.3.0

Cost-Benefit 105

Cost-Benefit Data-driven Software Testing 105

AWS Big Data

DECEMBER 23, 2024

At the heart of this ecosystem lies Kafka, specifically Amazon MSK, which serves as the backbone for their data integration systems. To stay competitive and efficient in the fast-paced financial industry, Fitch Group strategically adopted an event-driven microservices architecture.

Data-driven 96

Data-driven Management Risk Big Data 96

DataKitchen

AUGUST 16, 2024

Data Pipeline Observability: Optimizes pipelines by monitoring data quality, detecting issues, tracing data lineage, and identifying anomalies using live and historical metadata. This capability includes monitoring, logging, and business-rule detection.

Marketing 126

Marketing Data Quality Testing Metadata 126

DataKitchen

MAY 10, 2024

Production: During the production cycle, oversee multi-tool and multi-data set processes, such as dashboard production and warehouse building, ensuring that all components function correctly and the correct data is delivered to your customers. Quickly locate and address data or process errors before they affect downstream results.

Metrics 126

Metrics Testing Data Quality Dashboards 126

DataKitchen

MAY 10, 2024

Production : During the production cycle, oversee multi-tool and multi-data set processes, such as dashboard production and warehouse building, ensuring that all components function correctly and the correct data is delivered to your customers. Verifying data completeness and conformity to predefined standards.

Data Quality 133

Data Quality Testing Software Dashboards 133

Domino Data Lab

JULY 20, 2022

Validations and tests are key elements to building machine learning pipelines you can trust. We've also talked about incorporating tests in your pipeline, which many data scientists find problematic. Enter Deepchecks - an open source Python package for testing and validating machine learning models and data.

Machine Learning 98

Machine Learning Testing Modeling Data Science 98

datapine

FEBRUARY 10, 2021

Your Chance: Want to test a social media dashboard software for free? A social media dashboard is an invaluable management tool that is used by professionals, managers, and companies to gather, optimize, and visualize important metrics and data from social channels such as Facebook, Twitter, LinkedIn, Instagram, YouTube, etc.

Dashboards 193

Dashboards Scorecard KPI Metrics 193

erwin

OCTOBER 8, 2020

The desire to modernize technology, over time, leads to acquiring many different systems with various data entry points and transformation rules for data as it moves into and across the organization. Map data movement: erwin DI’s Mapping Manager defines data movement and transformation requirements via drag-and-drop functionality.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

DataKitchen

OCTOBER 20, 2023

Example 2: The Data Engineering Team Has Many Small, Valuable Files Where They Need Individual Source File Tracking In a typical data processing workflow, tracking individual files as they progress through various stages—from file delivery to data ingestion—is crucial.

Insurance 173

Insurance Metadata Data-driven Data Quality 173

Smart Data Collective

FEBRUARY 14, 2023

They test the product and find bugs that turn customers away. Game analysts are exclusively engaged in testing and reporting, and the elimination of identified problems falls on the shoulders of the development team. Data integrity control. Creation of hypotheses and their testing.

Big Data 134

Big Data Data Analytics Analytics Testing 134

Smart Data Collective

NOVEMBER 10, 2021

Analyze the originating source data, along with the target database. Test the conversion in at least three iterations and quality check the results. Implement the plan by converting (or transforming) the data into the formatting required by the target database. Issues Related to Data Migration.

Testing 137

Testing Data Integration Software Modeling 137

CIO Business Intelligence

JANUARY 5, 2023

Many customers find the sweet spot in combining them with similar low code/no code tools for data integration and management to quickly automate standard tasks, and experiment with new services. Customers also report they help business users quickly test new services, tweak user interfaces and deliver new functionality.

IT 130

IT Cost-Benefit Testing Dashboards 130

AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. We observed that our TPC-DS tests on Amazon S3 had a total job runtime on AWS Glue 4.0

Testing 103

Testing Data Lake Cost-Benefit Data Integration 103

DataKitchen

DECEMBER 20, 2020

DataOps Engineers implement the continuous deployment of data analytics. They give data scientists tools to instantiate development sandboxes on demand. They automate the data operations pipeline and create platforms used to test and monitor data from ingestion to published charts and graphs.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

CIO Business Intelligence

JUNE 24, 2024

Companies pour millions into AI initiatives, only to find themselves mired in pilot purgatory — endless cycles of testing and tweaking with no tangible results. These 10 strategies cover every critical aspect, from data integrity and development speed, to team expertise and executive buy-in.

Data Quality 124

Data Quality ROI Data Integration Metrics 124

Jet Global

JANUARY 22, 2021

It allows organizations to dive right in and view Longview Tax using their own entities and account structures, while also testing the values from their workpapers. This step helps to identify any changes that might need to be made either to Longview Tax’s processes or the data that are provided in the loader files. System setup.

Testing 98

Testing Software Reporting Forecasting 98