BIA ASSIGNMENT

QUE: Which of the two i.e. OLTP and OLAP, more helpful in strategic decisions? Why?

Ans

Online Transaction Processing System (OLTP)

OLTP System deals with operational data. Operational data are those data  involved in the operation of a particular system.

Example: In a banking System, you withdraw amount from your account. Then Account Number, Withdrawal amount, Available Amount, Balance Amount, Transaction Number etc are operational data elements.

Operational Data

Operational data are usually of local relevance

Frequent Updates

Normalized Tables

Point Query

In an OLTP system data are frequently updated  and queried. So quick response to a request is highly expected. Since the OLTP systems invlove large number of update quiries, the database tables are optimized for write operations.

To prevent data redundancy and to prevent update anomalies the database tables are normalized.Set of tables that are normalized are fragmented.Normalization makes the write operation in the database tables more efficient.

Operational data are usually of local relevance.It involves Queries accessing individual tuple(individual record).These type of queries are termed as point queries.

Examples for OLTP Queries:

What is the Salary of Mr.John?

Withdraw Money from Bank Account : It perform update operation if money is withdrawed from account.

What is the address and email id of the person who is the head of maths department?

 

Online Analytical Processing (OLAP)

OLAP deals with Historical Data or Archival Data. Historical data are those data that are archived over a long period of time. Data from  OLTP are collected over a period of time and store it in a very large database called Data warehouse. The Data warehouses are highly optimized for read (SELECT) operation. 

Example: If we collect last 10 years data about flight reservation, The data can give us many meaningful information such as the trends in reservation. This may give useful information like peak time of travel, what kinds of people are traveling in various classes (Economy/Business)etc.

Analytical Query: Online Analytical Processing (OLAP) quries are of  analytical form. Query need to access large amount of data and require huge number of aggregations. It access large number of records from database tables and perform the required operation based on this.

Historical Data or Archival Data

Infrequent updates

Analytical queries require huge number of aggregations

Integrated data set with a global relevance

Updates are very rare in a Data warehouse.OLAP quiries will give aggregated information about the things happend in the past over a period of time and this will help the management in strategic decision making. Hence OLAP Queries are of  having  significant importance in strategic decision making.

Examples for OLAP Queries

How is the profit changing over the years across different regions ?

Is it financially viable continue the production unit at location X?

Online Analytical Processing (OLAP) systems are targeted to provide more complex query results than traditional OLTP or database systems. Unlike database queries, however, OLAP applications usually involve analysis of the actual data. They can be thought of as an extension of some of the basic aggregation functions available in SQL. This extra analysis of the data as well as the more imprecise nature of the OLAP queries is what really differentiate OLAP applications from traditional database and OLTP applications. OLAP tools may also be used in DSS systems.

OLAP is performed on data warehouses or data marts. The primary goal of OLAP is to support ad hoc querying needed to support DSS. The multidimensional view of data is fundamental to

OLAP applications. OLAP is an application view, not a data structure or schema. The complex nature of OLAP applications requires a multidimensional view of the data. The type of data accessed is often (although not a requirement) a data warehouse.

There are several types of OLAP operations supported by OLAP tools:

Slice Dice Roll up Drill down

OLTP System OLAP System

Source of data Operational data; OLTPs are the original source of the data.

Consolidation data; OLAP data comes from the various OLTP Databases

Purpose of data

To control and run fundamental business tasks

To help with planning, problem solving, and decision support

What the data Reveals a snapshot of ongoing business processes

Multi-dimensional views of various kinds of business activities

Inserts and Updates

Short and fast inserts and updates initiated by end users

Periodic long-running batch jobs refresh the data

Queries Relatively standardized and simple queries Returning relatively few records

Often complex queries involving aggregations

Processing Speed

Typically very fast Depends on the amount of data involved; batch data refreshes and

complex queries may take many hours; query speed can be improved by creating indexes

Space Requirements

Can be relatively small if historical data is archived

Larger due to the existence of aggregation structures and history data; requires more indexes than OLTP

Database Design

Highly normalized with many tables

Typically de-normalized with fewer tables; use of star and/or snowflake schemas

Backup and Recovery

Backup religiously; operational data is critical to run the business, data loss is likely to entail significant monetary loss and legal liability

Instead of regular backups, some environments may consider simply reloading the OLTP data as a recovery method