Remove Data Architecture Remove Data Integration Remove Data-driven Remove Metadata
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Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

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IBM named a leader in the 2022 Gartner® Magic Quadrant™ for Data Integration Tools

IBM Big Data Hub

The only question is, how do you ensure effective ways of breaking down data silos and bringing data together for self-service access? It starts by modernizing your data integration capabilities – ensuring disparate data sources and cloud environments can come together to deliver data in real time and fuel AI initiatives.

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How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

Businesses are constantly evolving, and data leaders are challenged every day to meet new requirements. Customers are using AWS and Snowflake to develop purpose-built data architectures that provide the performance required for modern analytics and artificial intelligence (AI) use cases.

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How Metadata Makes Data Meaningful

erwin

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

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You Cannot Get to the Moon on a Bike!

Ontotext

Next, I will explain how knowledge graphs help them to get a unified view to data derived from multiple sources and get richer insights in less time. This requires new tools and new systems, which results in diverse and siloed data. And each of these gains requires data integration across business lines and divisions.

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How Knowledge Graphs Power Data Mesh and Data Fabric

Ontotext

The data ecosystem today is crowded with dazzling buzzwords, all fighting for investment dollars. A survey in 2021 found that a data company was being funded every 45 minutes. Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience.