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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

If you include the title of this blog, you were just presented with 13 examples of heteronyms in the preceding paragraphs. This is accomplished through tags, annotations, and metadata (TAM). My favorite approach to TAM creation and to modern data management in general is AI and machine learning (ML).

Strategy 267
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Simplify and Improve Analytics with Self-Serve Data Prep!

Smarten

Business users cannot even hope to prepare data for analytics – at least not without the right tools. Gartner predicts that, ‘data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ So, why is there so much attention paid to the task of data preparation?

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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Ontotext

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

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Don’t let your data pipeline slow to a trickle of low-quality data

IBM Big Data Hub

With traditional approaches , data issues are reported by data users as they try to access and use the data and may take weeks to fix, if they’re found at all. starts at the data source, collecting data pipeline metadata across key solutions in the modern data stack like Airflow, dbt, Databricks and many more.

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What’s the Current State of Data Governance and Automation?

erwin

The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability. And close to 50 percent have deployed data catalogs and business glossaries.

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IBM named a leader in The Forrester Wave™: Enterprise Data Fabric, Q2 2022

IBM Big Data Hub

The ability to compose and re-use data services with IBM’s data fabric on IBM Cloud Pak for Data allows you to tackle a variety of use cases such as multi-cloud data integration, governance and privacy, customer 360, and MLOps and Trustworthy AI. Providing the semantic. Providing the semantic.

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How to enable trustworthy AI with the right data fabric solution

IBM Big Data Hub

Organizations are increasingly depending upon artificial intelligence (AI) and Machine Learning (ML) to assist humans in decision making. The right data fabric solution will naturally support these pillars and help you build trustworthy AI models. Comprehensive, trusted data sets.