datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

Data Quality 241

Data Quality Metrics Data-driven Management 241

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes. usr/local/airflow/.local/bin/dbt

Data Warehouse 110

Data Warehouse Testing Data Quality Reporting 110

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Management 84

Management Data Warehouse Digital Transformation Dashboards 84

CIO Business Intelligence

DECEMBER 22, 2022

DataOps in practice To make the most of DataOps, enterprises must evolve their data management strategies to deal with data at scale and in response to real-world events as they happen, according to Dunning and Friedman. They also note DataOps fits well with microservices architectures.

Analytics 130

Analytics Machine Learning Software Data Quality 130

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. How does Data Virtualization manage data quality requirements? In forecasting future events.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Rocket-Powered Data Science

MARCH 20, 2023

In fact, by putting a single label like AI on all the steps of a data-driven business process, we have effectively not only blurred the process, but we have also blurred the particular characteristics that make each step separately distinct, uniquely critical, and ultimately dependent on specialized, specific technologies at each step.

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324