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 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

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 94

Data Warehouse Data Lake Analytics Data Science 94

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

MAY 1, 2023

Data Environment First off, the solutions you consider should be compatible with your current data architecture. We have outlined the requirements that most providers ask for: Data Sources Strategic Objective Use native connectivity optimized for the data source. addresses). Build your first set of reports.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52