What are the differences and similarities between OLAP and OLTP systems?

OLAP systems typically consist of four main components: - ???????? ????????????: The core engine powering the OLAP system, often requiring data transformation and preparation using ETL tools. - ???????? ????????????????: An optional intermediary layer that connects to the data warehouse, reducing unnecessary workloads and enabling easier data modeling. - ???????? ??????????: Multidimensional data models (HyperCube) with the downside that they are inflexible once built, requiring remodeling for any warehouse changes. - ???????? ???????????????? ??????????: Tools that help stakeholders in analyzing data within the OLAP Cube.

OLTP : Transaction Heavy systems like a regular banking application OLAP: Read heavy systems where writes are limited like a dashboard displaying analytics

When designing any database, understanding the use and intent is foundational. In OLTP (Online Transaction Processing), you are designing for application performance and transaction processing. The focus in OLTP is on handling a high volume of transactions in real-time, typically involving the use of normalized data structures, reducing redundancy, and allowing for smaller, related tables. *A pitfall I've observed in OLTP is when someone unfamiliar with data design designs for the screen they're looking at; this should be avoided. OLTP still requires a deep understanding of good data design and release managemen

OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing) are distinct data modeling techniques. OLTP, focused on handling frequent, short transactions like orders or financial transactions, emphasizes quick, efficient data processing and focuses on more highly normalized data structures to maintain data integrity and reduce redundancy. Compared to OLAP thatcaters to more complex queries for data analysis, such as trends and forecasting. It is a more denormalized approached, organizing data into multidimensional structures. Thus, OLTP excels in transactional efficiency (Insert Order, Update Order...), while OLAP specializes in analytical efficiency (What are total Sales?, What do we predict to sell...).

OLTP contains Transactional data while OLAP contains Aggregated data. OLTP can exist alone while OLAP has dependency on OLTP data. OLTP systems typically consists of most recent data while OLAP maintains historical data. OLAP provides analysis on Trends and Patterns while OLTP provides limited analysis possibilities.

One of the key differences is the timeliness of data. OLTP systems maintain real-time or near-real-time data, ensuring that every transaction is immediately reflected in the database. In contrast, OLAP systems might operate on data that's updated less frequently, such as nightly or weekly, depending on ETL schedules. This difference is crucial for designing systems where both immediate transactional accuracy and comprehensive historical analysis are required, like in financial services or e-commerce analytics.

OLAP system is design to analytics needs like reports or business intelligence cases; while OLTP system supports operational activities from business. Independently both are designed and implemented; the matter is how they interact Among themselves to help in its work. How OLTP system make sure data quality by business to OLAP system, it can help to fast, consistent and realistic knowledge to guide all business activities; so OLAP system can use to create great data products can be used in OLTP system to retain and build loyalty into users (generating more operations and money.) Data modeling can help to improve the interaction among them, if teams use well.

In my experience in SAP BW data warehouse we used to have ECC OR S4HANA as OLTP systems while BW datawarehose is acting as OLAP. All the transactional data is loaded into dimensions, attributes and hierarchy tables in BW OLAP systems. There are reporting and visualization tools which are built on top of OLAP system. Data warehouse data is stored in a denormalized way vs ECC transactional OLTP system is storing data in row format in a normalized format. OLAP environment data is stored in a aggregated summarised format so that in the reporting tools data can be read more efficiently. OLTP is more for operational data store Vs OLAP is for data reporting and data analysis. Data is loaded to OLAP from OLTP with ETLs Informatica, datastage etc

OLTP <> OLAP - Operations: Based on INSERT, UPDATE, DELETE <> Based on SELECT to aggregate data for reporting - Response time: Millisec <> Sec, min, or hrs depending on the amt of data to process - Design: Industry-specific, such as retail, manufacturing <> Subject-specific, such as sales, inventory, or marketing - Space reqs: Generally small if historical data is archived <> Generally large due to aggregating large datasets - Backup & recovery: Regular backups required to ensure business continuity and meet legal & governance requirements <> Lost data can be reloaded from OLTP db as needed in lieu of regular backups - Productivity: Increases productivity of end users <> Increases productivity of business managers, data analysts, executives