Data Warehousing in Light of Data Mining at Corporate Database Systems

Data warehouses work as the central database repository in which the information arrives from various data sources. Data flows into the warehouse from a transactional system that controls the inflow and outflow of data and other relational DBMS. These data may be structured, unstructured, or semi-structured.

In a typical big data environment, these data are produced, ingested, and transformed to access the pieces of data they want easily. They process the same for business intelligence and decision making. By merging all information from various destinations into one place, the organization utilizing data warehousing platforms can easily analyze their market performance and customer needs holistically. Further, it will help to ensure that all information is made available.

Data warehousing is needed at the base for data mining to be made possible. Data mining is looking for the data patterns that may lead to better business performance and profit.

Different types of data warehouses 

There are three major types of data warehouses:

1. Enterprise data warehouse

Also known as EDW, enterprise data warehouses are centralized data repositories. It provides high-end decision-making support enterprise-wide. EDW also offers a highly unified and centralized approach to representing and organizing enterprise data. It also offers the database administrators the ability to classify the available data according to the subject and give access based on various data divisions.

2. Operational data stores

Another type of data warehouse is operational data store or ODS, which is primarily the data storage needed when there is no data warehouse or OLTP systems out there to support the organizations’ reporting needs. In the case of ODS, a data warehouse is getting refreshed in real-time. So, it is preferred widely for routine activities like storing employee records and operational reports.

3. Datamart

You can consider data mart as a subset of a data warehouse. Data marts are designed for a specific line of business, like finance or sales etc. In any given independent data mart, the data can be collected from various sources directly.

Stages of data warehousing

When it all started first, the organizations were using the simplest forms of data warehousing. However, as time progressed, more and more sophisticated usages of data warehousing were initiated as below.

  • Offline operational DBs.
  • Offline data warehouses
  • Real-time data warehouses
  • Integrated data warehouses etc.

At the integrated stage, data warehouses get continuously updated while the operational systems are performing various transactions. With this, data warehouses generate the transactions needed to be sent back to the operational systems to ensure continuity of the operational processes.For data warehousing support, contact for an expert consultation.

Data warehouse concepts

Here are some of the major concepts/components of a data warehouse which the users should be aware of.

  • Load manager

Load manager is also known as the front-end component. It can perform all operations related to the extraction and loading of data into a warehouse. These operations include various transformations of data to enter into the data warehouse.

  • Warehouse manager

The warehouse manager is the entity that performs the data warehouse data related operations. It manages the operations as the data analysis to ensure consistency, create views and indexes, generate aggregations and denormalization, merge and transform the source data, and archive and back up the data.

  • Query manager

When load manager is the front-end component, query manager is considered as the backend. It can perform all operations based on user queries. The primary operation of these data warehouse components is to direct the queries to the most appropriate tables and schedule the query execution accordingly.

  • Tools for end-user access

Under this toolset, you can find various categories as

  1. Data reporting tools
  2. Querying tools
  3. App development tools
  4. EIS tools
  5. Data mining tools
  6. OLAP tools etc.

Data warehouses are used by all types of enterprise users like:

  • The business decision-makers who want to gain actionable insights from historical and market data.
  • The users who want to customize the complex processes and obtain information from various data sources.
  • People need the simplest technology to access their data anytime, anywhere.
  • For those who want a more systematic approach to decision making.
  • The users who want a faster performance on a huge volume of data as for reports, charts, grids, etc., can use a data warehouse as useful.
  • If you want to unveil the hidden patterns of data flows and groups.

Major industries where the data warehouse is largely used

Here are some of the common industries where data warehousing is largely used.

  • Airlines: in the airline systems, data warehousing is used largely for operations management as crew allocation, analyzing route profitability, tracking the frequent flyers promotions, etc.
  • Banking: In the banking sector, data warehousing’s ideal usage is to manage the available resources. Few banks also use data warehousing for market research, performance analysis in banking product sales, and operational efficiency.
  • Healthcare: Healthcare is one of the most crucial sectors leveraging data warehousing to strategize the procedures and predict the possible outcomes. IT also helps generate patient reports, share data for insurance processing, provide medical aid service, etc.
  • Public sector: In the case of public sector organizations, data warehousing is ideally used for gathering intelligence for better administration of projects. Data warehouses will help governments and administrative agencies to track and analyze the tax records and health policies etc., of each individual.
  • The insurance sector: Data warehouse in insurance and investment sectors is used to closely analyze various data patterns and trends and track the market movements.
  • Retail sector: In retail chains, various data warehousing technologies can be used for effective marketing and distribution. It helps track various items, buying patterns of the customers, promotions, and determining the pricing policy.

Along with these, data warehousing has many other applications too in telecommunication, hospitality, critical care, rescue operations, and so on. You can find customized data warehousing solutions for each of these purposes and customize the data warehousing tools to meet your specific needs.

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