Data storage and management is necessary for managerial operations to make rational business decisions. With the continuous flow of data in an organisation, a Data Warehouse (DW) can help in acting as a central repository of all the data from various sources. Data flows into a Data Warehouse from the transactional system and other databases.

The existing data undergoes processing and transformation that generates accessible data in the Data Warehouse using Business Intelligence tools such as SQL (Structured Query Language) clients and spreadsheets.

Data warehousing merges all the information from various sources into one consolidated & comprehensive database. Merging all the information into a single location, an organisation can analyse the customer`s wants, needs and other specifications.

A Data Warehouse Solutions makes data mining possible. Data mining is the process of identifying patterns in data that might lead to higher profits.

SECTOR-WISE Data Warehouse USAGE

Airline

In the Airline industry, numerous data such as route, pilot information, passenger information, flight specifications, weather forecast details and other such data can be stored in a Data Warehouse which can be utilised for operational purposes such as assigning the crew, analysing the best possible route for generating more profits, finding the best pilot services and so on.

Banking

In the banking sector, data such as bank account details, transaction details, customer database, document verification, generation of ATM pin numbers, and other such data can be stored in Data Warehouse which can be used for management of the available resources on the desk in an effective way to increase the efficiency. A few banks also use this for market research, performance analysis and product categorization.

Healthcare

The healthcare sector uses Data Warehouse for storing patient information, treatment details, doctors, medicines, pathological data which can be used for strategizing and forecasting the possible outcomes, generating patient’s treatment reports, sharing data with insurance companies, medical aid services, etc…

Public sector

In this sector, Data Warehouse is used for storing health records, policy records, and other data which can be used for gathering intelligence. It helps government agencies in maintaining and analysing health records, health policy documents and other such important data for every patient.

Investment and Insurance sector

In this sector, the Data Warehouses stores the investment details, investor`s details, stock market data, insurance policy data and so on which can be used to analyse the data patterns, trends of the customers, stock market inflow and outflow, and to track market movements.

Retail

In the retail sector, Data Warehouse stores inventory information, store details, sales count, billing information and other such data which is used for further distributing and marketing. It also helps to track items, analyse customer purchase patterns, promotions and also used for determination of pricing policies.

Telecommunication

A Data Warehouse can store call information, phone numbers, telecommunication service provider details, service distributor data which can be used in the telecommunication sector is for product promotions, sales decisions and to make distribution decisions.

Hospitality Industry

This Industry utilizes data stored in the Data Warehouse to design and estimate their advertising and promotional activities where they want to reach their target customers based on their customer feedback and travel patterns of them.

IMPLEMENTATION OF Data Warehouse

Implementation of a Data Warehouse is a series of activities that are requires to create a completely functioning Data Warehouse system after identifying, classifying, analysing, designing, and consolidating the data with respect to the requirements of the business. The various phases of implementing a Data Warehouse are as follows.

Determination of business objectives

The first step is to determine the objectives of the business such as sales targets, production targets, financial plans, promotions that are planned for marketing the product/service & administrative plans that are to be enforced.

Collection and analysis of the existing information

The second step is to collect the required data for the pre-set business objectives that are to be analysed. The data for collection and analysis can include reports, summaries, and survey results or any sort of usable data in an organisation.

Identifying the entities and processing

The next big step to implement a Data Warehouse is to identify the entities which require segregation and focus on the processing of the collected-analysed data by jotting down the factors that influence them.

Construction of a conceptual model-

Once the data has been identified and processed in accordance to the business objectives, a conceptual model needs to be designed that includes a detailed tabulation of the causes & effects of the possible outcomes in the business.

Locating the data sources

When the conceptual model is complete, the data sources need to be consolidated into the data structures-Structured, unstructured and semi-structured data. Once the consolidation is done, the Data Warehouse is almost ready to be installed.

Tracking the data duration

The last and final step to implement a Data Warehouse is to track the data for concluding the operation as per the business objectives. By tracing this, the duration can be analysed which can give space for planning and execution of the business goals.

BENEFITS OF HAVING A DATA WAREHOUSING SYSTEM

Data Warehousing systems can empower business intelligence

Data warehousing can provide data from various sources that can aid in the management and decision making of the business. A combination of Data Warehouse and Business Intelligence tools can result in a flawless business strategy by enhancing the business in terms of market segmentation, inventory management, financial management, and sales promotions to targeted and prospective customers.

Saving time & energy by using Data Warehouse-

A Data Warehouse allows business users to get access to any form of critical data from any source at any time within a short duration. This ensures best decision making in no time since retrieving the data from multiple sources can create a time lag. Lesser support from the IT will be needed for this. Data warehousing can also reduce costs in terms of paying the salaries of IT professionals and can use that money for a long-term investment of installing a Data Warehouse.

Data warehousing enriches the Data Quality and Consistency

Implementing a Data Warehouse system includes the conversion of data from various sources into a common format.  Data from each department is standardized and each department will produce results that are in par with other departments. This gives an added advantage of confidence and accuracy of data which is fundamental for a stable business.

Provides Historical Intelligence-

A data warehousing system stores a large amount of historical data that can be analysed at any time to forecast the prospects.

Enhances data quality and consistency-

Implementing a Data Warehouse system includes the conversion of data from various sources into a common format.  Data from each department is standardized and each department will produce results that are on par with other departments.

Other benefits-

Data Warehousing has other benefits such as proving competitive advantage & streamlining the flow of information in the organisation.

BEST DATA WAREHOUSING TOOLS & TECHNOLOGIES 2020

Here are some of the prominent and efficient tools that can be used to implement a data warehousing system;

Oracle-

Oracle offers a wide range of choices including data warehousing solutions for both on-premises and cloud. This helps in the optimization of the customer experience by increasing the operational efficiency.  

BigQuery-

BigQuery by Google is a supreme data warehousing tool. This tool reduces the duration for storing and querying the datasets by means of enabling high speed SQL queries. This also controls and monitors the project and offers the feature of viewing or querying the data.

Amazon RedShift-

Amazon Redshift is a cost-efficient and simple tool that can analyse various types of data using standard SQL and BI (Business Intelligence) tools. This tool uses the technology of query-optimization for running complex queries against petabytes of structured data.

IBM – DataStage

The IBM-DataStage is a business intelligence tool that integrates data across numerous enterprise systems. It uses a high-performance parallel framework that can run on the cloud or on-premises. This tool also supports metadata management and global business connectivity.

Microsoft SSIS-

The SQL Server Integration Service is a Data warehousing tool that is basically used for the performance of ETL (Extraction Transformation & Loading) operations. The SQL Server Integration also consists of a good set of built-in tasks.

Teradata Corporation-

Teradata is the only commercially available Massively Parallel Processing (MPP) Data Warehouse tool. This tool is one of the best for viewing large data and managing them.

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