OLAP vs. OLTP- Understand Their Key Uses andDifferences

OLAP vs. OLTP- Understand Their Key Uses andDifferences

The terms OLAP and OLTP are confusing to many business owners when it comes to data science and data processing systems. When it comes to understanding their functions, you first should know what each of these terms means and how they are different from each other.

Today, businesses and people are living in a data-driven era where companies deploy data to make informed and smarter decisions. They help them respond quickly to the dynamic needs that should be placed on the top of their to-do list. You will often see data of Kisscartoon working in new business service offerings of the company, such as ride-sharing software apps and powerhouse systems that drive both e-commerce and in-store business transactions.

Data processing systems – OLAP and OLTP

Data processing systems fall under two types-

  1. Online analytical processing or OLAP, and
  2. Online Transaction Processing or OLTP.

The major difference between the two is that one deploys data to gain invaluable insights while the other is completely operational. However, both of them can be used in innovative ways to resolve data issues.

Experienced IT experts and database administrators (DBAs) caution businesses that the question here is not to determine what to choose but how can you make the best use of these data processing system types for your needs.

OLAP or Online Analytical Processing

Online analytical processing or OLAP refers to a system that performs multi-dimensional analysis quickly on large data sets. Generally, this data is derived from a data mart or a data warehouse, or some other data store that is centralized for the business. It is perfect for data mining, analytical calculations that are complex in nature, business intelligence, and reporting functions for the business like the forecast of sales, financial analysis, and budgeting.

The nucleus of the OLAP databases is mostly the OLAP cube. It permits the business to report, query, and analyze data of a multi-dimensional nature quickly.

Understanding data dimension

Data dimension is a single element of a specific dataset. For instance, the sales figures might have multiple dimensions related to the time of the year, region, product models, and lots more.

This OLAP cube extends a row-by-column type format of the schema used in traditional relational databases that add layers for the other data dimensions. For instance, while the layer on top of the cube may organize the sales per region, data analysts can drill down into layers that depict sales by province or state, city, or specific stores. The aggregated and historical data for OLAP is generally stored in the snowflake schema or star schema.

Online Transactional Processing or OLTP

Online Transactional Processing or OLTP assists in the real-time execution of big numbers of data transactions by a large number of individuals online via the Internet. Experts from credible database consulting, management, and administration company,,states that these systems are the heroes of the many daily transactions that people carry out. They are behind ATMs to the in-store purchases to reservations for hotels and flights. OLTP can also trigger transactions of a non-financial nature like text messages and changes in a password.

The OLTP system deploys the relational database for carrying out the following tasks-

  1. Processes a large set of simple transactions that are generally deletions to the data, updates, and insertions.
  2. Enables a multi-user access to similar data-keeping data integrity intact.
  3. Supports very fast processing with quick response times that are measured in milliseconds.
  4. Offers data sets that are indexed for quick searching, querying, and retrieval.
  5. Be available with regular incremental backups 24/7 x 365 days.

Several companies deploy OLTP systems for providing data for OLAP. In short, IT specialists and DBAs sum up by saying both OLAP and OLTP are indispensable in the modern data-driven era.

The key difference between OLAP and OLTP systems

The key distinction between these two data processing systems lies in their respective names- analytical and transactional. Each of these systems is optimized for that specific type of data processing.

The OLAP data processing system is optimized for carrying out analysis of complex data for smarter and better decision-making for the business. This system is resorted to by business analysts, data scientists, and knowledge workers. They support the business intelligence or BI of the organization, other applications that support decision-making, and data mining.

The OLTP system, on the other hand, is generally optimized for the processing of a very large number of data transactions designed for frontline workers, like for example, bank tellers, cashiers, clerks in charge of hotel reservations, etc., or for applications that deploy self-service skills like travel reservations, online banking, and eCommerce.

OLAP Versus OLTP- which one should you use?

Selecting the right data processing system for your specific needs actually depends upon what your objectives are. Ask yourself the following questions-

  1. Do you require a single platform for your business insights? (OLAP helps you to unlock value from large data sets.)
  2. Do you need to manage transactions on an everyday basis?
  3. (OLTP has been designed for the faster processing of a large number of data transactions for every second.

Experienced DBAs and IT experts state that in the case of conventional OLAP tools, one needs expertise in the field of data modeling. At the same time, the business requires good cooperation across several business units. On the contrary, the OLTP data processing system is more business-critical in nature. If there is any downtime in this system, it will disrupt online transactions, loss of sales or revenue, and lots of damage to your brand’s reputation.

Mostly, organizations in the modern era prefer using both the OLAP and OLTP data processing systems. IT specialists and skilled DBA consultants sum up by saying that the OLAP data processing system can be used for analyzing data leading to improvements in the business process for the OLTP systems. Incorporating both of them in your business is a smart and prudent choice to gain a strategic edge in the market.

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