Business intelligence (BI) is a set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information for business purposes. BI can handle large amounts of information to help identify and develop new opportunities. Making use of new opportunities and implementing an effective strategy can provide a competitive market advantage and long-term stability.
Business intelligence can be used by enterprises for the data analysis of business information. BI technologies provide historical, current, and predictive views of business operations. Common functions of business intelligence technologies include reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics. BI technologies can handle large amounts of structured and sometimes unstructured data to help identify, develop, and otherwise create new strategic business opportunities. They aim to allow for the easy interpretation of these big data. Identifying new opportunities and implementing an effective strategy based on insights can provide businesses with a competitive market advantage and long-term stability.
Business intelligence can be used by enterprises to support a wide range of business decisions ranging from operational to strategic. Basic operating decisions include product positioning or pricing. Strategic business decisions involve priorities, goals, and directions at the broadest level. In all cases, BI is most effective when it combines data derived from the market in which a company operates (external data) with data from company sources internal to the business such as financial and operations data (internal data). When combined, external and internal data can provide a complete picture which, in effect, creates an "intelligence" that cannot be derived from any singular set of data. Amongst myriad uses, business intelligence tools empower organizations to gain insight into new markets, to assess demand and suitability of products and services for different market segments, and to gauge the impact of marketing efforts.
BI applications use data gathered from a data warehouse (DW) or from a data mart, and the concepts of BI and DW combine as "BI/DW"or as "BIDW". A data warehouse contains a copy of analytical data that facilitate decision support.
Big data is very quickly becoming a vital tool for businesses and companies of all sizes. The availability and interpretation of big data has altered the business models of old industries and enabled the creation of new ones. Data scientists are responsible for breaking down big data into usable information and creating software and algorithms that help companies and organizations determine optimal operations. As big data continues to have a major impact on the world, data science does as well due to the close relationship between the two.
Data mining
Using databases, statistics and machine learning to uncover trends in large datasets.
Reporting
Sharing data analysis to stakeholders so they can draw conclusions and make decisions.
Performance metrics and benchmarking
Comparing current performance data to historical data to track performance against goals, typically using customized dashboards.
Descriptive analytics
Using preliminary data analysis to find out what happened.
Querying
Asking the data specific questions, BI pulling the answers from the datasets.
Statistical analysis
Taking the results from descriptive analytics and further exploring the data using statistics such as how this trend happened and why.
Data visualization
Turning data analysis into visual representations such as charts, graphs, and histograms to more easily consume data.
Visual analysis
Exploring data through visual storytelling to communicate insights on the fly and stay in the flow of analysis.
Data preparation
Compiling multiple data sources, identifying the dimensions and measurements, preparing it for data analysis.
To make business intelligence an effective solution for business units—or anyone else without that technical knowledge—the solution has to be as user friendly and accessible as possible for all levels of employees throughout an organization.
Augmented Analytics
A smart solution can make business intelligence easy—one with augmented analytics employing embedded machine learning. This kind of solution can help users in gathering, analysing, interpreting, and conveying information—simplifying and automating tasks.
A smart solution can make business intelligence easy—one with augmented analytics employing embedded machine learning. This kind of solution can help users in gathering, analysing, interpreting, and conveying information—simplifying and automating tasks.
It should be able to automate data preparation, collecting information from multiple sources and consolidating it, accelerating the process and reducing the chance of errors. It should also be able to augment your analysis by recommending new data sets to include in the review for more accurate results.
A smart solution that lets users quickly and easily search for what they need and get to the data directly with the capability for users to ask questions and receive answers in human language.
Some solutions even offer a semantic layer that allows users to access data and modify requests and data set parameters using common business terms.
A user should also be able to easily access predictive analytics and forecasting to see patterns and forecast future outcomes and trends—without the need to know coding. A smart solution with embedded machine learning can offer that advantage and more.
Data Visualization
Many smart solutions come with data visualization, which provides the capability to automatically transform data into pie charts, graphs, or other type of visual presentation. Users can quickly and easily see and understand patterns, relationships, and emerging trends that might go unnoticed with a spreadsheet of raw numbers.
With data visualization, users can get new and unique insights by creating rich data mashups. They can craft stories around their business with high-impact visuals. No specialized training is required to interpret what’s presented in the graphics.
Data is pulled from internal and external sources. Then, users have a choice. They can decide between numerous options which graphic is best for presenting the data. Or they can allow the application to automatically make a recommendation based on data results.
Our focus of Business Intelligence ultimately seeks to show customers how to be most effective with their information management and discover business opportunities for their data.
We analyse business model, strategies, business requirements, and existing data and provide the estimations and suggest required tools to fulfil the requirements.
We provide various BI In-premises and Cloud level solutions such that data migrations, building data marts/data warehouse, ad-hoc/dynamic reporting, dashboards, data visualizations, statistical analysis, descriptive/predictive analysis, Key Performance Indicatorsto our business customers to take decisions effectively in right time and right manner.
We also provide 24 X 7 (3 shifts) services to support to the existing production systems of our Business Customers.
We can provide consulting services to our business users when and where required.
