Data Quality Data Transformation Marketing Reporting 
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.
Ontotext
MARCH 20, 2024
Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Studies reveal that businesses lose significant time and opportunities due to missing integrations and poor data quality and accessibility.
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CIO Business Intelligence
JANUARY 24, 2024
Undervaluing unstructured data Much of the data organizations accumulate is unstructured, whether it’s text, video, audio, social media, images, or other formats. These information resources can hold enormous value for enterprises , enabling them to gain new insights about customers and market trends.
erwin
APRIL 29, 2020
These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.
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.
Peter James Thomas
OCTOBER 30, 2018
Note: Not all of the organisations I have worked with or for have had a C-level Executive accountable primarily for Marketing. Where they have, I have normally found the people holding these roles to be better informed about data matters than their peers. The same goes in general for Marketing Managers.
erwin
SEPTEMBER 17, 2020
According to erwin’s “2020 State of Data Governance and Automation” report , close to 70 percent of data professional respondents say they spend an average of 10 or more hours per week on data-related activities, and most of that time is spent searching for and preparing data. Faster Business Turnaround.
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