Data Governance Data Transformation Document Modeling 
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.
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. Creating a High-Quality Data Pipeline.
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datapine
SEPTEMBER 29, 2022
Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business. These needs are then quantified into data models for acquisition and delivery. This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling.
AWS Big Data
APRIL 19, 2023
This allows for a new way of thinking and new organizational elements—namely, a modern data community. However, today’s data mesh platform contains largely independent data products. Even with well-documented data products, knowing how to connect or join data products is a time-consuming job.
IBM Big Data Hub
JANUARY 9, 2024
Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.
Alation
OCTOBER 27, 2022
Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Jason: How do you use these models?
Alation
JUNE 28, 2022
This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.
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