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Major Difference Between Data Mining and OLAP

Data Mining and OLAP
Data Mining and OLAP

Difference Between Data mining and OLAP

Learn and Understand the complete detail about the difference between Data Mining and OLAP

What is Data Mining?

Information mining is defined as a process used to extract usable records from a large set of any raw records.

Some key features of data mining are:

  • Automatic sample prediction primarily based on-trend.
  • Predictions based on possible results.
  • The advent of decision-oriented statistics.
  • Cognizance of big statistics and databases for evaluation.
  • Clustering primarily based on a group of facts no longer previously known.

Data Mining Documentation

For extra information approximately ODM, see the subsequent documentation:

1:  Oracle information mining standards

2: The “Data mining capabilities” section within the oracle sq. reference

3: DBMS_datamining, DBMS_data_mining_transform, and DBMS_predictive analytics in          oracle database pl/square packages and types reference

4: Oracle data mining java API reference (Javadoc)

5: Oracle facts mining administrator’s guide

The Benefits of Data Mining:

Data mining has ended up a device in addressing many complicated enterprise troubles and possibilities, and has been validated successfully in many unique regions, consisting of:

  • Customer relationship control
  • Retail industry
  • Manufacturing and production
  • The travel enterprise

Customer relationship control:

Its purpose to construct one-on-one relationships with clients by way of growing an intimate understanding of their wants and needs. With all the facts that are generated from numerous events (product inquiries, income, product reviews), there are numerous different approaches data mining can offer greater perception.

  • Become aware of most in all likelihood shoppers /Responders of the latest products and services.
  • Understand the foundation reasons for consumer attrition to enhance patron retention.
  • Discover time-variant institutions among products and services to maximize income and patron value.
  • Become aware of the maximum worthwhile clients, and their preferential needs to bolster relationships and maximize income.

The Retail Industry:

  • Predict accurate income volumes at precise stock stages.
  • Become aware of income relationships between specific product types.
  • Forecast intake stages of different product types to optimize logistics and subsequently maximize sales.
  • Discover interesting styles into the motion of products, mainly ones with a quick shelf life, in a delivery chain by using studying sensory and RFID data.

Manufacturing and Production:

  • Predict machinery failures earlier than they arise with the aid of the use of sensory statistics, in an effort to allow situation-primarily based maintenance.
  • Identify commonalities and anomalies in manufacturing systems to optimize production potential.
  • Find out novel styles to perceive and enhance product great.

The travel enterprise (airlines or hotels):

  • Useful to are expecting income of different offerings (seat kinds in airplanes, type of inn rooms) to optimally rate offerings to maximize revenues as a function of yield management.
  • The forecast called for specific places to higher allocate confined organizational resources.
  • Discover the maximum profitable customers and offer them customized offerings to maintain their repeat commercial enterprise.
  • Hold valuable employees by way of identifying and acting on the basis causes for attrition.

What is Online Analytical Processing (OLAP)?

OLAP is a laptop processing that permits a consumer to easily and selectively extract and think about data from different points of view. It allows users to investigate database information from more than one database structure at one time. OLAP data is saved in multidimensional databases.

Some key features of OLAP are:

  • Multidimensional views of records.
  • Help for complicated calculations.
  • Time intelligence.

OLAP Documentation:

1: Oracle OLAP software developer’s guide

2: Oracle OLAP reference

3: Oracle OLAP DML reference

4: Oracle OLAP developer’s guide to the OLAP API

5: Oracle OLAP Java API reference

6: Oracle OLAP analytic workspace java API reference

The Benefits of OLAP:

Basing an OLAP machine at once on the oracle server offers the following blessings:

  • Scalability
  • Availability
  • Manageability
  • Backup and Restoration
  • Security

Scalability:

Oracle database OLAP is exceptionally scalable. in an ultra-modern environment, there may be a high-quality boom alongside 3 dimensions of analytic packages: a range of users, length of data, the complexity of analyses. There are more users of analytical programs, and that they need to get entry to more records to perform more sophisticated evaluation and target Advertising. as an instance, a smartphone organization may need a client size to encompass elements such as all cell phone numbers as a part of an application that is used to investigate consumer turnover.

Availability:

Oracle database includes many functions that aid high availability. one of the maximum widespread is partitioning, which lets in management of specific subsets of tables and indexes, in order that control operations have an effect on most effective small pieces of these data systems. by using partitioning tables and indexes, statistics management processing time is decreased, thus minimizing the time information is unavailable. some other function assisting high availability is portable tablespaces. with transportable tablespaces, large statistics units, along with tables and indexes, may be delivered with nearly no processing to other databases. this permits extraordinarily speedy information loading and updates.

Manageability:

Oracle permits you to precisely manage resource usage. the database aid supervisor, as an example, presents a mechanism for allocating the assets of a data warehouse among extraordinary sets of quit-customers. recall a surrounding where the advertising branch and the sales branch proportion an OLAP machine. using the database aid supervisor, you should specify that the advertising department receives at least 60 percent of the CPU sources of the machines, whilst the income department receives 40 percent of the CPU sources. you could additionally similarly specify limits on the whole range of energetic sessions, and the degree of parallelism of individual queries for each branch.

Backup and Restoration:

  • Oracle gives a server-controlled infrastructure for backup, restore, and restoration obligations that permit simpler, safer operations at terabyte scale.
  • Information associated with the backup, repair, and healing operations are maintained by the server in a recovery catalog and mechanically use as part of those operations. This reduces the administrative burden and minimizes the possibility of human mistakes.
  • Backup and restoration operations are fully incorporated with partitioning. Person partitions, while located in their personal tablespaces, may backed up and restored independently of the opposite walls of a table.
  • Oracle consists of a guide for incremental backup and restoration of the use of restoration supervisor, permitting operations to be completed efficaciously inside instances. proportional to the number of changes, as opposed to the general length of the database.
  • The backup and recovery era is extraordinarily scalable and gives tight interfaces to enterprise-main media control subsystems. This provides for green operations which could scale up to address very massive volumes of statistics. open systems for extra Hardware options and employer-degree structures.

Security:

Just because the demands of actual-global transaction processing required oracle to develop strong functions for scalability, manageability, and backup and recovery, they lead oracle to create industry-main protection functions. the security functions in oracle have reached the highest ranges of U.S. government certification for database trustworthiness. Oracles exceptional grained get admission to manipulating feature, permits cell-stage protection for OLAP customers. First-rate Grained get admission to control works with minimum burden on query processing, and it permits green centralized security management.

Difference between OLAP and Data Mining

 

Difference between OLAP and Data Mining
Difference between OLAP and Data Mining

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