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6 dimensions of data quality boost data performance
Poor data quality can lead to costly mistakes and bad decision making. The six dimensions of data quality ensure accurate, complete, consistent, timely, valid and unique data.
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Understand Microsoft Copilot security concerns
Microsoft Copilot raises security concerns around unauthorized or unintentional data access. Prevent leaks with vigilant oversight and comprehensive user access reviews.
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How to make a metadata management framework
Don't wait until you have a metadata management problem to address the issue. Put a metadata management framework in place to prepare for potential issues.
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InfluxData targets performance, adds self-managed version
The time series database specialist's update addresses performance to better handle complex real-time workloads and includes a new option for on-premises and private cloud users.
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Data science and analytics Get Started
Data literacy training requires a dual approach
Data literacy training is a flexible learning process. Organizations can tailor training for their teams, but individuals can find educational resources to better their skills.
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Database Management News
InfluxData targets performance, adds self-managed version
The time series database specialist's update addresses performance to better handle complex real-time workloads and includes a new option for on-premises and private cloud users.
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Data Warehousing Evaluate
On-premises vs. cloud data warehouses: Pros and cons
Data warehouses increasingly are being deployed in the cloud. But both on-premises and cloud data warehouses have pluses and minuses to consider, as explained here.
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Exploding interest in GenAI makes AI governance a necessity
With more employees of organizations now using artificial intelligence tools to inform business decisions, guidelines that ensure their safe and secure use are critical.
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Data Integration Get Started
How to use Microsoft Copilot in Power BI
Enable Microsoft Copilot in Power BI to automate key features using generative AI capabilities that improve insights and accelerate decision-making.
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Data Governance Manage
6 dimensions of data quality boost data performance
Poor data quality can lead to costly mistakes and bad decision making. The six dimensions of data quality ensure accurate, complete, consistent, timely, valid and unique data.
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Generative AI shines spotlight on data governance and trust
Generative AI creates new opportunities for how organizations use data. Strong data governance is necessary to build trust in the data AI models use.
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Cloud database comparison: AWS, Microsoft, Google and Oracle
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Top 6 data fabric tools providers
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What is data architecture? A data management blueprint
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Problem Solve
6 dimensions of data quality boost data performance
Poor data quality can lead to costly mistakes and bad decision making. The six dimensions of data quality ensure accurate, complete, consistent, timely, valid and unique data.
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Data lake governance: Benefits, challenges and getting started
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7 steps to create a data loss prevention policy
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6 data privacy challenges and how to fix them
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Understand Microsoft Copilot security concerns
Microsoft Copilot raises security concerns around unauthorized or unintentional data access. Prevent leaks with vigilant oversight and comprehensive user access reviews.
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How to make a metadata management framework
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10 top vector database options for similarity searches
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How to use a data governance maturity model
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E-Handbook | November 2021
Chief data officer challenges mount amid calls for more value
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Enterprise data lakes hold the key to actionable insights
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Metamorphosis of Kafka Confluent event streaming technologies
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E-Handbook | June 2020
Data integration technologies unify multiple data stores
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Big data security management embraces governance, privacy
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Data Management/Data Warehousing Basics
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Successful data operations follow a data governance roadmap
Implementing a data governance strategy requires a roadmap to keep everyone on track and overcome challenges. Follow eight key steps for best results.
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SQL
Structured Query Language (SQL) is a standardized programming language that is used to manage relational databases and perform various operations on the data in them.
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What is data validation?
Data validation is the practice of checking the integrity, accuracy and structure of data before it is used for or by one or more business operations.
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InfluxData targets performance, adds self-managed version
The time series database specialist's update addresses performance to better handle complex real-time workloads and includes a new option for on-premises and private cloud users.
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Data management strategies
Couchbase launches database tools to foster AI development
The vendor's new columnar capabilities and mobile-based vector search are aimed at helping customers access unstructured data to inform models and applications.
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Data management strategies
Cribl positions for IPO with $319M in latest funding round
The observability specialist's latest financing, along with strong recurring revenue and customer growth, helps set the vendor up to go public pending further financial milestones.
Data Management Definitions
- What is Structured Query Language (SQL)?
- What is data validation?
- What is a data flow diagram (DDF)?
- What is denormalization and how does it work?
- What are data silos and what problems do they cause?
- What is a data architect?
- What is a vector database?
- What is master data management (MDM)?