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 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics?

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 111

Metadata Data Lake Visualization Data Transformation 111

DataKitchen

OCTOBER 25, 2022

The goal of DataOps Observability is to provide visibility of every journey that data takes from source to customer value across every tool, environment, data store, data and analytic team, and customer so that problems are detected, localized and raised immediately. A data journey spans and tracks multiple pipelines.

Testing 130

Testing Data-driven Visualization Dashboards 130

AWS Big Data

JANUARY 30, 2025

Our approach The migration initiative consisted of two main parts: building the new architecture and migrating data pipelines from the existing tool to the new architecture. Often, we would work on both in parallel, testing one component of the architecture while developing another at the same time.

Data Warehouse 54

Data Warehouse Data Architecture Machine Learning Data Transformation 54

AWS Big Data

NOVEMBER 13, 2023

As Gameskraft’s portfolio of gaming products increased, it led to an approximate five-times growth of dedicated data analytics and data science teams. Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

Occam's Razor

OCTOBER 19, 2010

If you can show ROI on a DW it would be a good use of your money to go with Omniture Discover, WebTrends Data Mart, Coremetrics Explore. If you have evolved to a stage that you need behavior targeting then get Omniture Test and Target or Sitespect. Experimentation and Testing Tools [The "Why" – Part 1]. and embrace Multiplicity.

Analytics 136

Analytics Testing Measurement Optimization 136

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 111

Data Strategy Strategy Data Governance Marketing 111

Sisense

AUGUST 6, 2020

Be sure test cases represent the diversity of app users. As an AI product manager, here are some important data-related questions you should ask yourself: What is the problem you’re trying to solve? What data transformations are needed from your data scientists to prepare the data?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

JANUARY 17, 2023

What if, experts asked, you could load raw data into a warehouse, and then empower people to transform it for their own unique needs? Today, data integration platforms like Rivery do just that. By pushing the T to the last step in the process, such products have revolutionized how data is understood and analyzed.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

AWS Big Data

JULY 31, 2023

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. AWS Glue is a serverless data integration and ETL service with the ability to scale on demand. Choose Save changes.

Sales 52

Sales Data Warehouse Visualization Testing 52

Alation

OCTOBER 28, 2021

This, in turn, empowers data leaders to better identify and develop new revenue streams, customize patient offerings, and use data to optimize operations. Too much access increases the risk that data can be changed or stolen. Remove Low Quality, Unused, or “Stale” Data.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 122

Data Lake Management Metrics Data Warehouse 122

CIO Business Intelligence

AUGUST 7, 2024

The Project Kernel framework utilizes templates and AI augmentation to streamline coding processes, with the AI augmentation generating test cases using training models built on the organization’s data, use cases, and past test cases. This enabled the team to expose the technology to a small group of senior leaders to test.

IT 119

IT Insurance Cost-Benefit Testing 119

FineReport

MARCH 31, 2024

Through meticulous testing and research, we’ve curated a list of the ten best BI tools, ensuring accessibility and efficacy for businesses of all sizes. In essence, the core capabilities of the best BI tools revolve around four essential functions: data integration, data transformation, data visualization, and reporting.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Smarten

JANUARY 4, 2018

Think of your data warehouse as an active repository that is ever changing as new data sources keep on getting added and existing data sources keep on getting updated. In order to manage the environment, an organization must dedicate resources to monitor and track ETL process, its data flow, data integration and data updates.

Data Warehouse 40

Data Warehouse OLAP Data Governance Optimization 40

AWS Big Data

DECEMBER 2, 2024

More companies have realized there is an opportunity to integrate, enhance, and present this SaaS data to improve internal operations and gain valuable insights on their data. From there, they can perform meaningful analytics, gain valuable insights, and optionally push enriched data back to external SaaS platforms.

Data Lake 105

Data Lake Testing Data Integration Metadata 105

BI-Survey

MARCH 6, 2025

While efficiency is a priority, data quality and security remain non-negotiable. Developing and maintaining data transformation pipelines are among the first tasks to be targeted for automation. However, caution is advised since accuracy, timeliness, and other aspects of data quality depend on the quality of data pipelines.

Data Warehouse 52

Data Warehouse Metadata Unstructured Data Data-driven 52

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Jet Global

MAY 1, 2023

Strategic Objective Create a complete, user-friendly view of the data by preparing it for analysis. Requirement Multi-Source Data Blending Data from multiple sources is compiled and the output is a single view, metric, or visualization. Data Transformation and Enrichment Data can be enriched for analysis.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

JULY 16, 2024

Apache Iceberg is an open table format for huge analytic datasets designed to bring high-performance ACID (Atomicity, Consistency, Isolation, and Durability) transactions to big data. It provides a stable schema, supports complex data transformations, and ensures atomic operations. What is Apache Iceberg?

Dashboards 52

Dashboards Data-driven Reporting Business Intelligence 52