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Steps Companies Should Take to Come Up Data Management Processes

Smart Data Collective

The process of managing data can be quite daunting and complicated. Data management is a set of processes and policies that organizations use to collect, store and share data. It involves understanding how the organization uses data and how the data is stored, and then working out what to do with it.

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Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms!

ElegantJ BI

In today’s business environment, most organizations are overwhelmed with data and looking for a way to tame the data overload and make it more manageable to help team members gather and analyze data and make the most of the information contained within the walls of the enterprise.

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Data Warehouse, Data Lake, Data Mart, Data Hub: A Definition of Terms!

ElegantJ BI

In today’s business environment, most organizations are overwhelmed with data and looking for a way to tame the data overload and make it more manageable to help team members gather and analyze data and make the most of the information contained within the walls of the enterprise. Data Warehouse.

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Top 20 Data Warehouse Best Practices in 2024

Astera

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

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Information Marts: Enabling Agile, Scalable, and Accurate BI

Astera

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

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Data Profiling: Types, Techniques and Best Practices

Astera

It includes format checks, range checks, and consistency checks to ensure data is clean, correct, and logically consistent. Understanding the Difference: Data Profiling vs. Data Mining Data profiling and data mining are two distinct processes with different objectives and methodologies.

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Data Extraction Tools: Bridging the Gap Between Unstructured and Structured Data

Astera

A voluminous increase in unstructured data has made data management and data extraction challenging. The data needs to be converted into machine-readable formats for analysis. However, the growing importance of data-driven decisions has changed how managers make strategic choices.