DATA WAREHOUSING vs DATA MINING | FREE IT NOTES | CAIIB 2022
IIBF conducts various exams, and CAIIB is one of them, which is conducted twice a year, once in June and again in November. For CAIIB, we have two mandatory subjects, ABM and BFM, along with one elective exam. Candidates have to choose one topic from an array of 6 subjects- information technology, Human Resource Management, risk management, rural banking, central banking, and retail banking. In this article, we will talk about information technology, its notes that we provide along with an insight into data warehousing vs data mining tools.
Information Technology (IT)
Information Technology (IT) refers to the creation, processing, storage, security, and sharing of all types of electronic data using computers, storage, networking, and other physical devices, infrastructure, and procedures. In contrast to the technology utilized for personal or leisure purposes, IT is usually used in the context of corporate activities. Computer technology and telecommunications are both included in commercial applications of IT.
Now that we are done discussing IT FREE NOTES, we can move further with the description of data warehousing and data mining tools.
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Data Warehousing
A data warehouse is where information can be kept for later use. It’s similar to a lightning-fast computer with a massive amount of data storage. Data is copied to the Warehouse from other organizations’ systems, where it can be fetched and conformed to eliminate errors. Advanced data-warehouse requests can be made here. The following are some of the most essential characteristics of a data warehouse:
The focus is on the subject
A data warehouse is organised by subject. It gives information about a subject rather than the company’s ongoing operations, and these subjects can include customers, suppliers, marketing, product, and promotion, among others. A data warehouse is primarily concerned with data modeling and analysis to assist a corporate organisation in making data-driven choices.
Time-Variant
The data warehouse’s various data sources provide information for a specific time period.
Complementary
A data warehouse is created by combining information from various sources, such as social databases, level papers, etc.
It is non-volatile
It means that data entered into the warehouse cannot be changed once entered.
Data Warehouse Benefits
- More precise data access
- Productivity and performance have improved.
- Cost-efficient
- Data that is consistent and of high quality
Tools used in data warehousing are
The software components needed to perform various processes on a huge volume of data are known as data warehousing tools. Data warehousing software is used to gather, read, write, and move massive amounts of data from many sources. Sorting, filtering, merging, aggregating, and other operations on databases, data stores, and data warehouses are also performed by data warehouse tools.
- CData Sync is a program that allows you to sync your data with your computer
All your Cloud/SaaS data may be easily replicated to any database or data warehouse in a matter of minutes. CData Sync is a user-friendly data pipeline that allows you to consolidate data from any application or data source into your preferred database or data warehouse.
- Integrate.io (Integrate.io) is a website that allows
Integrate.io is an e-commerce-specific Data Warehouse Integration Platform. Integrate.io assists e-commerce businesses in creating a 360-degree perspective of their customers, providing a single source of truth for data-driven choices, boosting customer insights through better operational insights, and increasing return on investment.)
- QuerySurge
RTTS developed the QuerySurge ETL testing system. It’s designed primarily for data warehouses and extensive data testing automation.
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Data Mining
Data mining tries to help businesses see business habits, trends, and linkages to make data-driven decisions. Knowledge Discovery in Database is another name for it (KDD). To uncover the relationship between the data, data mining techniques employ AI, statistics, databases, and machine learning systems. Business-related queries that are normally time-consuming to settle can benefit from data mining techniques.
Data mining has a few key features
The following are some of the critical aspects of data mining:
- It makes use of pattern recognition software that is automatically generated.
- It foresees what will happen.
- Large data sets and databases are the focus of this research.
- It generates data that can be used.
Data Mining Benefits
Market Research
Data mining can forecast the market, assisting businesses in making decisions. It can, for example, predict who is interested in purchasing which things.
Detection of Fraud
Data mining techniques can assist in determining which cellular phone conversations, insurance claims, and credit or debit card purchases are fraudulent.
Financial Market Analysis
Data mining techniques are commonly employed to assist in the modeling of financial markets.
Analysis of Trends
Analyzing the current market trend is a strategic benefit because it aids in cost reduction and manufacturing processes that align with market demand.
Some data mining tools are
- Rapid Miner
- Oracle Data Mining
- IBM SPSS Modeler
- Knime
- Python
- Orange
- Kaggle
- Rattle
- Weka
- Teradata
- H2O
- Apache Spark
- Sisense
- Xplenty
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CAIIB STUDY MATERIAL
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