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

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. Azure Blob Storage serves as the data lake to store raw data.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

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 92

Data Warehouse Data Lake Analytics Data Science 92

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

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

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

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 Transformation Business Intelligence 52

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

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 Modeling Metrics 52

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 135

Analytics Testing Measurement Optimization 135

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 102

Data Lake Management Metrics Data Warehouse 102

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

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

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

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 Sales 52

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