Information is critical to the management and running of any business. As data grows in volume, traditional technologies are no longer adequate to manage it. Fortunately, technologies are rapidly evolving to meet new needs. Most businesses need operational as well as analytical data. They serve different purposes and yet they are complimentary. A strong data management solution will need both kinds.
Running your business versus managing your business
There’s a difference in the information required to run a business and manage a business. The difference in application type influences the design of the database.
Operational systems manage high volume transaction processing and data warehousing systems support analytical processing. Operational systems deal with current data and data warehousing systems deal with historical data. Operational systems deal with simple transactions, whereas a data warehouse handles more complex, unpredictable queries. The one is more process-oriented and the other more subject-oriented.
Operational data is the data that comes from the day-to-day operations of a business. Customers, inventory, and purchase data fall into this data category. The data is quite straightforward and usually looks quite similar for most businesses.
An operational data store centralizes all sources of data. For example, it may include data from a billing system that records customer information and a transaction system that records purchases as they occur. The ODS contains data from both systems and enables more effective reporting and analytics than when data is separated into individual systems. An ODS is useful for operational queries about the current state of the business.
Business analysis tools that need data closer to real-time can query the ODS data as it comes from the various source systems. Real-time data allows a business to diagnose a problem and fix it.
Modern operational data stores use various advances such as in-memory execution and cloud-based databases to improve functionality, scalability, and speed.
Strategic and planning functions
Analytical data is more complex and may look different for different businesses. It is best stored in a data system designed for data mining and aggregation, such as a data warehouse. A data warehouse may not contain the most up-to-date data but it is more stable and less volatile than an ODS.
The design supports the storage of and access to large amounts of data, thus supporting analytical activities where large quantities of data are necessary. It is possible to compare data from many systems, departments, and locations in one place.
A data warehouse contains consistent data required for a retrospective, more sophisticated analysis that supports strategic and planning functions. Comprehensive, long-term decision-making is made possible by observing long-term data trends.
Real-time versus snapshots of the state of data at historic points in time
Looking at data in real-time versus looking at a snapshot of the state of data at a historic point in time offers different benefits to a business.
Operational reporting requires access to real-time data. Operational applications capture and store data in real-time. A business needs to deliver products and services required by its client base on a daily, weekly, or monthly basis. Managing this process effectively requires access to actionable insights from data that’s as close to real-time as possible to make the best decisions.
For example, as it holds the most recent version of data, combining it with the right business intelligence tools means that it is possible to monitor customer activities, track orders, manage inventory, and more.
The data required to make strategic, planning decisions
A comparison of snapshots of the state of data at certain historic points in time can reveal changes and trends that occur over time. Analytical reporting will use the total number of units sold or total sales for a month, rather than all the sales transactions that take place in a certain period.
The information necessary to make strategic decisions involves being able to predict changes in levels and type of demands, availability of resources, and the influence of potential external factors, such as the economic or legislative environment. Strategic organizational decisions take a business along the right path towards its objectives. Analytical reporting can help with the development of new product pricing, marketing campaigns, and marketing segmentation.
‘What?’ versus ‘what if?’ reports
If the purpose of an application is to answer questions like “What time did the order ship?” an operational database can provide quick access to an answer. Cupertino Times discusses app development technology trends of 2021. The use of apps is growing rapidly and they need access to real-time data.
If ‘what if?’ questions need answering, then the data in a data warehouse is more useful. In fact, complex queries can slow down an operational database and as the data constantly changes, the answers may be inaccurate.
No redundancy versus data integration
Operational systems avoid redundant data and tables are small to improve backup times, data updates, and query performance. Data that isn’t referenced often can be moved into separate databases or into tables that only contain historical data. Operational systems also avoid using indexes because they can negatively affect the performance of updates and inserts.
Analytical data is stored structures that are non-normalized and more likely to display data duplications and redundancies. It is possible to categorize the data in many different ways to give different snapshots of the data. As decision-support systems have low update requirements but big data volumes, indexing improves query performance.
A final word
An operational database provides data for a data warehouse and updates are made frequently, offering the current view of the latest transactions. This operational data is the information necessary to run the day-to-day operations of a business. The data required for data analysis and decision-making resides in data warehouse systems, which organize and presents information in specific formats to suit the needs of various users. Most businesses use a mix of both types of data in their data management strategies. Hence, they are not only able to run daily operations but make complex business decisions regarding business management.