[Business Intelligence App For Mac
Sharif Garmon
Business intelligence (BI) consists of strategies and technologies used by enterprises for the data analysis and management of business information.[1] Common functions of BI technologies include reporting, online analytical processing, analytics, dashboard development, data mining, process mining, complex event processing, business performance management, benchmarking, text mining, predictive analytics, and prescriptive analytics.
BI tools can handle large amounts of structured and sometimes unstructured data to help organisations to 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, and help them take strategic decisions.[2]
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.[3]
Among 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.[4]
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"[5]or as "BIDW". A data warehouse contains a copy of analytical data that facilitates decision support.
The earliest known use of the term business intelligence is in Richard Millar Devens' Cyclopdia of Commercial and Business Anecdotes (1865). Devens used the term to describe how the banker Sir Henry Furnese gained profit by receiving and acting upon information about his environment, prior to his competitors:
Throughout Holland, Flanders, France, and Germany, he maintained a complete and perfect train of business intelligence. The news of the many battles fought was thus received first by him, and the fall of Namur added to his profits, owing to his early receipt of the news.
When Hans Peter Luhn, a researcher at IBM, used the term business intelligence in an article published in 1958, he employed the Webster's Dictionary definition of intelligence: "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."[7]
In 1989, Howard Dresner (later a Gartner analyst) proposed business intelligence as an umbrella term to describe "concepts and methods to improve business decision making by using fact-based support systems."[8] It was not until the late 1990s that this usage was widespread.[9]
with analysis to evaluate complex corporate and competitive information for presentation to planners and decision makers, with the objective of improving the timeliness and the quality of the input to the decision process."[10]
According to Forrester Research, business intelligence is "a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making."[11] Under this definition, business intelligence encompasses information management (data integration, data quality, data warehousing, master-data management, text- and content-analytics, et al.). Therefore, Forrester refers to data preparation and data usage as two separate but closely linked segments of the business-intelligence architectural stack.
Though the term business intelligence is sometimes a synonym for competitive intelligence (because they both support decision making), BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes, and disseminates information with a topical focus on company competitors. If understood broadly, competitive intelligence can be considered as a subset of business intelligence.[13]
Business intelligence and business analytics are sometimes used interchangeably, but there are alternate definitions.[14] Thomas Davenport, professor of information technology and management at Babson College argues that business intelligence should be divided into querying, reporting, Online analytical processing (OLAP), an "alerts" tool, and business analytics. In this definition, business analytics is the subset of BI focusing on statistics, prediction, and optimization, rather than the reporting functionality.[15]
Business operations can generate a very large amount of data in the form of e-mails, memos, notes from call-centers, news, user groups, chats, reports, web-pages, presentations, image-files, video-files, and marketing material. According to Merrill Lynch, more than 85% of all business information exists in these forms; a company might only use such a document a single time.[16] Because of the way it is produced and stored, this information is either unstructured or semi-structured.
Therefore, when designing a business intelligence/DW-solution, the specific problems associated with semi-structured and unstructured data must be accommodated for as well as those for the structured data.
In a 2013 report, Gartner categorized business intelligence vendors as either an independent "pure-play" vendor or a consolidated "mega-vendor".[23][non-primary source needed] In 2019, the BI market was shaken within Europe for the new legislation of GDPR (General Data Protection Regulation) which puts the responsibility of data collection and storage onto the data user with strict laws in place to make sure the data is compliant. Growth within Europe has steadily increased since May 2019 when GDPR was brought. The legislation refocused companies to look at their own data from a compliance perspective but also revealed future opportunities using personalization and external BI providers to increase market share.[24][permanent dead link]
Businesses and organizations have questions and goals. To answer these questions and track performance against these goals, they gather the necessary data, analyze it, and determine which actions to take to reach their goals.
Business intelligence includes data analytics and business analytics but uses them only as parts of the whole process. BI helps users draw conclusions from data analysis. Data scientists dig into the specifics of data, using advanced statistics and predictive analytics to discover patterns and forecast future patterns.
Traditional business intelligence is still a common approach for regular reporting and answering static queries. However, modern business intelligence is interactive and approachable. While IT departments are still an important part of managing access to data, multiple levels of users can customize dashboards and create reports on little notice. With the proper software, users are empowered to visualize data and answer their own questions.
For example, financial services firm Charles Schwab used business intelligence to see a comprehensive view of all its branches across the United States to understand performance metrics and identify areas of opportunity. Access to a central business intelligence platform allowed Schwab to bring its branch data into one view. Now branch managers can identify clients that may have a change in investment needs. And leadership can track if a region's performance is above or below average and click in to see the branches that are driving that region's performance. This leads to more opportunities for optimization along with better customer service for clients.
Another example is the meal-kit service HelloFresh which automated its reporting processes because its digital marketing team spent far too much time on it each month. With the help of Tableau, HelloFresh saved 10 to 20 working hours per day for the team, and made it possible for them to create much more segmented and targeted marketing campaigns.
Many self-service business intelligence tools and platforms streamline the analysis process. This makes it easier for people to see and understand their data without the technical know-how to dig into the data themselves. There are many BI platforms available for ad hoc reporting, data visualization, and creating customized dashboards for multiple levels of users. We have outlined our recommendations for evaluating modern BI platforms so you can choose the right one for your organization. One of the more common ways to present business intelligence is through data visualization.
Arguably one of the most useful tools in BI are dashboards, which allow complex data to be aggregated and viewed all in one place. These dashboards can have different purposes, such as for complex analysis or stakeholder buy-in. The challenge is building the best dashboard for your needs.
As you can imagine, this is important for BI as businesses create more and more data by the year, and BI platforms have to keep up with the increasing demands made on them. A good platform will grow with increasing demands. But if not maintained, dashboards and data sources may fall behind as big data evolves.
Business intelligence is continually evolving to keep pace with business needs and technology, so each year, we identify current trends to keep users up-to-date on innovations. Realize that artificial intelligence and machine learning will continue to grow, and businesses can integrate the insights from AI into a broader BI strategy. As companies strive to be more data-driven, efforts to share data and collaborate will increase. Data visualization will be even more essential to work together across teams and departments. This article is just an introduction to the world of business intelligence. BI offers capabilities for near real-time sales tracking, allowing users to discover insights into customer behavior, forecast profits, and more. Diverse industries like retail, insurance, and oil have adopted BI, and more are joining each year. BI platforms adapt to new technology and the innovation of its users.
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