New digital technology has dynamically inflated the volumes of data being generated across different industries. Going forward, data volumes are expected to rise up to 85% every year, across all sectors. Increasing data requirements and the limitations of traditional database systems are leaving decision makers overwhelmed with incorrect, inadequate, misleading and inconsistent data.
Limitations of Traditional Database Systems
- Data Inconsistency: Data redundancy leads to data inconsistency. It occurs due to the same data items that appear in more than one file and do not get updated simultaneously in every file.
- Data Dependence: The applications in traditional database systems are data dependent i.e., the file organization – its physical location and retrieval are directed by the needs of a specific application.
- Unstructured Data: Unstructured data (textual or non-textual) results in irregularities and anomalies that makes it hard to interpret & understand information using the traditional database systems.
- Issue of Security: Enforcing security constraints in a traditional database system is very difficult, since the application programs are added to the database system in an ad-hoc manner.
- Data Isolation: Data is scattered in different files, and these files may be in different format, which makes it difficult to write new application program and retrieve data.
- Lack of Data Integration: Since independent data file exists, users face difficulty in getting information on any ad hoc query that requires accessing the data stored in many files.
Why Business Intelligence?
To capitalize on the Big Data trend, legions of companies have started utilizing Business Intelligence to capture and analyze the complex new data sets. Now the question is – how does Business Intelligence (BI) helps businesses gain valuable data insights?
BI is a technology-driven process for analyzing data and providing actionable information to help business managers, corporate executives and other end users make strategic, more informed business decisions. It gives organizations the opportunity to discover data correlations and patterns that would have otherwise remained hidden. This means organizations now have access to more accurate information using a range of BI tools, including:
- Alteryx
- Tableau
- R
- SPSS
- SAS
- Hadoop
- Cognos
What are the different techniques in Business Intelligence?
Business Intelligence uses a range of data refining techniques including data mining, data warehousing, data analytics, data reporting and visualization to reveal patterns and transform information into valuable insights.
- Data Mining: Data mining is the extraction of data from large databases – a technology that helps businesses to focus on the most important information in their data warehouses. Data mining tools help to predict the future behaviors and trends, allowing companies to make practical, accurate decisions.
- Data Warehousing: Data warehouse is an integrated, subject-oriented collection of data specifically structured for query and analysis. Data warehousing solutions help businesses gain deeper data insights at a lower cost of ownership. The goal is to provide the clear starting points that they can use to redesign their data architecture.
- Big Data Analytics: Big data analytics refers to the process of gathering, organizing & analyzing large sets of data to discover patterns and other valuable information. Using advanced analytics techniques, businesses can better understand the key information contained within the data.
- Data Reporting and Visualization: Reports generated by Business Intelligence tools efficiently collect and present information to support planning, management and decision making process. Data Visualization in the form of charts and graphs is a convenient way to interpret and understand data.
Advantages of Business Intelligence
Over the last couple of years, an increasing number of businesses have invested in Business Intelligence to help them centralize, access and better understand the key business metrics including sales. BI data can include historical data, as well as the new gathered information from source systems to predict future performance and support the strategic decision-making processes.
The potential benefits of Business Intelligence programs include:
- Driving new revenues
- Identifying market trends
- Increasing operational efficiency
- Optimizing internal business processes
- Gaining competitive advantages
- Improving and accelerating decision making
- Finding business problems that need to be addressed