Data Fabric has released the Data Fabric Analytics Platform that helps companies that operate at different locations across the globe to standardize on a single analytics platform for business intelligence.
What is Data Fabric?
Data Fabric is a data warehousing platform to provide analytics using big data storage, visualization, and BI. Therefore, the product helps enterprises manage, analyze and serve their big data in real-time from any source or system.
Why is data fabric necessary?
At first, Data Fabric helps companies to move data from disparate systems and to create a real-time environment that can be use for analytics. Therefore, by combining a data warehouse, business intelligence (BI) tools, and real-time analytics into a single platform, Data Fabric accomplishes this. However, it utilizes the following technologies:
Data Fabric Analytics Platform- Besides, the Data Fabric Analytics Platform (DFA) is a hosted analytics platform that combines clients’ master data, pre-built analytics, and the power of Data Fabric’s data warehousing infrastructure. Also, It allows users to define their own rules and processes to create their own structure for data exploration and performance management.
This platform offers best-in-class business intelligence tools that include:
Data Fabric Application Programming Interface (API)- The Data Fabric API is an open-source tool that integrates with the Oracle RDBMS. It includes the following 3 components:
1. Data Source API- Data Source API connects to any source data;
2. Analytics API- Data Source API’s analytics tools allow users to add and remove data, query data and build complex queries.
3. Data Warehouse API- The Data Warehouse SDK Connects directly with the Oracle RDBMS, thereby allowing all the software components to work in conjunction.
The data fabric includes 2 major components: data warehouse and real-time analytics.
The Data Fabric Analytics Platform(DFA) is a hosted analytics platform that combines clients’ master data, pre-built analytics, and the power of Data Fabric’s data warehousing infrastructure. It allows users to define their own rules and processes to create their own structure for data exploration and performance management. The DFA uses a metadata server to store its metadata that is used by all the software components in order to communicate with each other.
The data warehouse is a platform for storing and managing data for performance management and analysis. In addition, this tool allows users to query their data by using SQL query capabilities.
Real-time analytics is a tool that permits users to explore, analyze and manage their master data in a near real-time and interactive manner, regardless of its location or the source system. Also, it uses Oracle BI Publisher to create reports and dashboards, and generate alerts.
- Data fabric’s main features
- Analytics capabilities
- Data Warehouse
- Real-time Analytics
- Data Integration and Master Data Management Capabilities.
Besides, It is built on a platform known as the “Oracle Big Data Appliance” (ODBA). The ODBA is Oracle’s open-source platform for managing/processing big data.
Data Fabric’s competitors
The Data fabric’s main rival is the Oracle BI Cloud. Data Fabric was launched in September 2011 and the BI Cloud was launched in October 2011. Therefore, the two are considered to be big data analytics providers with similar capabilities.
1. A retailer is analyzing the sales data to find potential customers with whom they can start a loyalty club. Therefore, it wants to get a view of its entire customer base.
2. A telecommunications operator is analyzing call data to identify network bandwidth that can be use more effectively
3. A bank is analyzing customer data to understand the customer’s behavior. Also, it wants to use this information to increase or decrease loan interest rates depending on what constitutes good behavior from a lending perspective.
Data Fabric in QA testing
A QA engineer in a software company wanted to test out his company’s online sales process that includes functions like logging in, viewing products and placing them into a web cart, and then again logging out. The problem he faced was that incomplete input from the user at first log in meant that the session timed out.
His initial solution was to use a number of test accounts with full credit cards. To test out each account, he would first log in as that account, fill out all the necessary fields and then click the submit button to see if the submitted details were saved or not. If they did save, it meant that he encountered an error while saving those particular details. Therefore, this was a tedious process and it would have taken too long to let him identify the cause of the problem.
The benefits of data fabric
1. Users can define their own rules and processes to create their own structure for data exploration and performance management.
2. The platform offers best-in-class business intelligence tools that include; Data Integration and Master Data Management, Dashboards, reporting, Collaboration, and BI on Hadoop.
3. The platform is built using open-source software components like Jaspersoft, Pentaho, HBase, MongoDB, etc.
4. Cloud-based architecture.
5. Provides a master data management tool that is integrated with all the other business intelligence tools.
6. Seamless integration with all the Oracle enterprise applications and Big Data solutions.
7. It can be use for both big data and small data analytics.
8. framework allows developers to use their programming skills to work with the platform.
Yes, it is true that both Oracle BI Cloud and Data Fabric have similar capabilities however, the BI Cloud is a hosted service while Data Fabric is an on-premise solution. This makes data fabric an ideal choice for enterprises that are not comfortable with the idea of hosting their data in the cloud.