Data Bolster

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    • Home
    • Our Services
      • Data Warehouse
      • Datamart
      • Data Transformation
      • Data Mapping & Migration
      • Data Profile & Enrichment
      • Data Cleansing
      • Data Analysis
      • Dashboard & BI
    • Industries
    • Our Product
    • Contact Us
Data Bolster

DataBolster

  • Home
  • Our Services
    • Data Warehouse
    • Datamart
    • Data Transformation
    • Data Mapping & Migration
    • Data Profile & Enrichment
    • Data Cleansing
    • Data Analysis
    • Dashboard & BI
  • Industries
  • Our Product
  • Contact Us

Data warehouse

A data warehouse is a centralized repository that stores structured data (database tables, Excel sheets) and semi-structured data (XML files, webpages) for the purposes of reporting and analysis. The data flows in from a variety of sources, such as point-of-sale systems, business applications, relational databases, and it is usually cleaned and standardized before it hits the warehouse. Because a data warehouse can store large amounts of information, it provides user with easy access to a wealth of historical data, which can be used for data mining, data visualization and other forms of business intelligence reporting.


Benefits of data warehouse

Reliable data, especially when aggregated over time, help users make smarter, more informed decisions about the way they run their organization—and data warehouses are what makes that possible. The benefits of enterprise data warehousing are myriad, but some of the most impactful advantages include: 

  • Consolidating data from multiple sources into one single source of truth
  • Storing and analyzing long-term historical data spanning months and years
  • Cleansing and transforming data so that it is accurate, consistent, and standardized in structure and form
  • Reducing query times when gathering data and processing analytics, which improves overall performance across systems
  • Efficiently loading data without having to deal with the costs of deployment or infrastructure
  • Securing data so that it is private, protected, and safe
  • Preparing data for analysis through data mining, visualization tools, and other forms of advanced analytics

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