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

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture.

Data Governance 82

Data Governance Business Objectives Strategy Data Quality 82

erwin

SEPTEMBER 17, 2020

For example, automatically importing mappings from developers’ Excel sheets, flat files, Access and ETL tools into a comprehensive mappings inventory, complete with auto generated and meaningful documentation of the mappings, is a powerful way to support overall data governance. Data quality is crucial to every organization.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Smart Data Collective

APRIL 29, 2020

A survey from Tech Pro Research showed that 70 percent of organisations already have a digital transformation strategy or are developing one. Solutions for the various data management processes need to be carefully considered. The techniques for managing organisational data in a standardised approach that minimises inefficiency.

Management 84

Management Data Warehouse Digital Transformation Dashboards 84

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

AWS Big Data

APRIL 19, 2023

Background The success of a data-driven organization recognizes data as a key enabler to increase and sustain innovation. The goal of a data product is to solve the long-standing issue of data silos and data quality. However, today’s data mesh platform contains largely independent data products.

Technology 80

Technology Data-driven Machine Learning Sales 80

DataRobot Blog

MARCH 10, 2022

This is currently a widespread strategy across the industry where we are seeing companies move from reactive to predictive inventory management and capacity planning. The first step in building a model that can predict machine failure and even recommend the next best course of action is to aggregate, clean, and prepare data to train against.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52