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Steps Companies Should Take to Come Up Data Management Processes

Smart Data Collective

These include, but are not limited to, database management systems, data mining software, decision support systems, knowledge management systems, data warehousing, and enterprise data warehouses. Some data management strategies are in-house and others are outsourced.

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5 Pain Points of Moving Data to the Cloud and Strategies for Success

Alation

This recent cloud migration applies to all who use data. We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment. The Five Pain Points of Moving Data to the Cloud.

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Most data processing tasks are completed using ETL (Extract, Transform, Load) or ELT (Extract, Load Transform) processes. Data classification, standardization, normalization, verification, validation, and deduplication are all examples of data processing tasks.

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How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale

AWS Machine Learning Blog

Organizations can search for PII using methods such as keyword searches, pattern matching, data loss prevention tools, machine learning (ML), metadata analysis, data classification software, optical character recognition (OCR), document fingerprinting, and encryption.

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Alation 2022.1: Customize Your Data Catalog

Alation

Lineage helps them identify the source of bad data to fix the problem fast. Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed). Time is money,” said Leonard Kwok, Senior Data Analyst, ARC.

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

Most data processing tasks are completed using ETL (Extract, Transform, Load) or ELT (Extract, Load Transform) processes. Data classification, standardization, normalization, verification, validation, and deduplication are all examples of data processing tasks.

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How foundation models and data stores unlock the business potential of generative AI

IBM Journey to AI blog

Foundation models can be trained to perform tasks such as data classification, the identification of objects within images (computer vision) and natural language processing (NLP) (understanding and generating text) with a high degree of accuracy.

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