Most organizations depend on operational data for critical operations like dashboarding and reporting purposes. It comes from different transactional systems of the organization before flowing into a central database.
The operational data provide the current data from multiple sources beneficial to most business operations. Technology is the driving force behind the effective analysis of operational data.
What is an operational data store
The ODS is the central database that provides the latest data from multiple systems for operational reporting. Organizations can combine data in its original format from the different sources into a single destination with the help of the operational data store.
What is a data warehouse
A data warehouse is a data management system that enables and supports business intelligence activities. It’s intended to perform queries and analysis solely. Data warehouse contains large amounts of historical data derived from a wide range of sources like the application log files.
How operational data stores work
Businesses use operational data stores to process reports from different departments like billing, security, marketing, and production. The end-users also use operational data stores to give them insights into the current trends of the organization.
Below is a brief overview of the ODS workflow:
Data collection
This is the first stage of the operational data store workflow where different data sources collect information. An excellent data source example is customer relations management (CRM) or enterprise resource planning tools. Most of these data sources operate independently of one another.
That means they don’t exchange data at any stage of the collection process. Data sources are often a mix of numerous technologies and dealers related to the business.
Data processing
The next stage is that the data then goes through ETL for processing. Here, the data is extracted and transformed. These transformations include cleaning the data, standardizing it, and loading it into the ODS for future analysis.
The ODS then integrates the real-time data to the various programs that the organization uses. They may include the dashboards and the BI tools.
Sending data to data warehouse
After the data is integrated, the remaining information is sent to the data warehouse. It’s typically done for archiving, storage, reporting, and analysis. The operational data store is designed to allow overwriting of the stored data. This will enable them to store large volumes of data compared to the data warehouse.
Differences between ODS and data warehouse
One of the most significant differences is that an OLTP system is used for transaction and processing queries. In contrast, the OLAP system is market-oriented and is used for data analysis by the company’s experts and managers. The operational data system handles current data that often are too detailed for simple decision making.
On the other hand, the data warehouse handles large amounts of historical information to provide the necessary facilities for summarization and aggregation. Data warehouses also store and manage data at different levels of granularity.
With the ODS, the system focuses mainly on the current information inside an enterprise without clearly defining the historical data in the multiple organizations. In contrast, the data store often snaps multiple versions of a database schema due to the evolutionary process of the company.
Lastly, the OLTP system generally embraces an entity-relationship data approach and an application-oriented database style, while an OLAP system generally adopts a snowflake model or star model. These differences clearly show that operational data stores are not replacing the data warehouses.
Importance of ODS
The stiff competition amongst different businesses is pushing many businesses to rely on data. For the companies to use the data collected successfully, the data needs to be analyzed and distributed efficiently to the respective workers. Below are a few importance of ODS.
Most organizations often enforce strict governance systems that restrict database access to specific company members. That’s through the use of fast and secure data rooms for carrying out transactions and collecting valuable insights. This approach makes it harder to share the company’s analytics with respective members.
Operational data provide stores are often used for secure data sharing across different departments in the organization. They prevent the users from tapping into data sources to obtain the data by allowing data to flow from the ODS to populate the various sources where needed.
The ODS provides a complete view of the data as the company has enhanced visibility into its data. Making informed decisions then becomes an easy task for most of the processes under review. The executive members of the organization can view data across multiple sources to ensure that they come up with a complete report.
Operational data store simplifies the analysis process of manipulating data. In this case, the company doesn’t have to track down the data needed manually across the different data sources. The process is just straightforward for the end-users streamlining the analysis process in data analysis. Data is also accessible through the centralized locations sparing the users from combing through disparate databases.
Many companies have a wide variety of data sources that do not communicate with one another. The data also comes through different formats. With the ODS, it’s possible to unify disparate systems that ensure that information is consolidated and merged, providing consistent data for practical analysis.
There is also access to real-time reporting with the operational data store. Companies need to respond as fast as possible as per the insight of the analyzed data. ODS gives access to the most updated information of the business.
Features of great ODS
Features of great ODS describe what you should look for when looking for one. Several solutions need to be implemented to fit the needs of the company. Some of the features of great ODS include cloud-native architecture, lightning-fast ingestion, zero maintenance, and full support.
The chances are that the team members will encounter many challenges when using the ODS, which is why it’s vital to have a comprehensive support center. This will help resolve issues that arise and access information for better understanding.
