Astera

MAY 25, 2023

Change management: Establish a standardized process for making changes to data sets. Changes should be logged, tested, and approved before being applied. Data quality: Regularly check data for issues like inaccuracies, inconsistencies, and incompleteness.

Big Data 40

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Astera

APRIL 24, 2024

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.

Data Governance 52

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CMW Lab Blog

NOVEMBER 9, 2023

. – Accuracy: Automation within a DMS significantly reduces the risk of human error in tasks such as data entry and document routing. This leads to consistent and error-free document management, improving data quality and reliability.

Documentation 52

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Astera

OCTOBER 10, 2023

Data mapping is the process of defining how data elements in one system or format correspond to those in another. Data mapping tools have emerged as a powerful solution to help organizations make sense of their data, facilitating data integration , improving data quality, and enhancing decision-making processes.

IBM Maintenance 52

IBM Maintenance IBM Support IBM cost Data Quality 52

Astera

MARCH 20, 2024

Enterprise data management (EDM) is a holistic approach to inventorying, handling, and governing your organization’s data across its entire lifecycle to drive decision-making and achieve business goals. Management of all enterprise data, including master data.

Data Management 52

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Tableau

SEPTEMBER 23, 2021

Low data discoverability: For example, Sales doesn’t know what data Marketing even has available, or vice versa—or the team simply can’t find the data when they need it. . Unclear change management process: There’s little or no formality around what happens when a data source changes.

Data Governance 91

Data Governance Government Data Quality Change Management 91

Tableau

SEPTEMBER 23, 2021

Low data discoverability: For example, Sales doesn’t know what data Marketing even has available, or vice versa—or the team simply can’t find the data when they need it. . Unclear change management process: There’s little or no formality around what happens when a data source changes.

Data Governance 79

Data Governance Government Data Quality Change Management 79

Ntara

JUNE 26, 2023

Consider your product data management challenges. Like most organizations, you may struggle with manual initiatives, poor data quality, and collaboration between employees and teams. Establishing a “read only” MAD for stakeholders is also a way to standardize your data dictionary and support data quality.

Data Management 52

Data Management Documentation Data Governance Government 52

Actian

DECEMBER 9, 2018

Unfortunately, even modern data warehousing tools have their shortcomings. Batch data loads lead to delays in current data. IT change-management policies meant to ensure data quality and security increases the development time for new insights.

Data Warehouse 40

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Data Pine

FEBRUARY 22, 2022

If you go in with the right mindset you will be prepared to address issues like complicated data problems, change management resistance, waning sponsorship, IT reluctance, and user adoption challenges. Clean data in, clean analytics out. Indeed, every year low-quality data is estimated to cost over $9.7

Business Intelligence 87

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Astera

JANUARY 12, 2024

Self-Serve Data Infrastructure as a Platform: A shared data infrastructure empowers users to independently discover, access, and process data, reducing reliance on data engineering teams. However, governance remains essential in a Data Mesh approach to ensure data quality and compliance with organizational standards.

Data Architecture 52

Data Architecture Data Warehouse Data Quality Government 52

Domo

JUNE 13, 2017

When people experience inconsistency (dissonance) such as conflicting information, they are motivated to dismiss the new evidence as erroneous rather than questioning their original data or opinion. Rather than automatically assuming you have a data quality issue, you may have a change management issue instead.

Big Data 52

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Insight Software

SEPTEMBER 26, 2023

Data Cleansing Imperative: The same report revealed that organizations recognized the importance of data quality, with 71% expressing concerns about data quality issues. This underscores the need for robust data cleansing solutions.

IBM Maintenance 52

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