Business Intelligence, or business intelligence, refers to all the technologies that allow companies to analyze data for the benefit of their decision-making.
Data analysis can be very useful in assisting companies in their decision making. To collect and analyze data, it is necessary to use a wide variety of tools and technologies: this is Business Intelligence .
Contents
Business Intelligence: what is business intelligence?
Business Intelligence: what are the benefits for companies?
Business Intelligence: what are the business intelligence tools?
Business Intelligence or business intelligence: what is the decision chain?
Business Intelligence: which personnel and which infrastructures to benefit from BI?
Business Intelligence: What Are the Potential Problems of Business Intelligence?
Business Intelligence: the best courses and training in business intelligence
Business Intelligence vs Big Data: What's the Difference?
What are the differences between Business Intelligence and Data Science?
Business Intelligence: what is business intelligence?
The term Business Intelligence (BI), or business intelligence, designates the applications, infrastructures, tools and practices providing access to information, and allowing to analyze information to improve and optimize decisions and performance. of a business . In other words, Business Intelligence is the process of analyzing data driven by technology to uncover information that can be used to help business leaders and other end users make more informed decisions.
Thus, BI brings together a wide variety of tools, applications and methodologies to collect data from internal systems and external sources, prepare them for analysis, develop them and launch queries. within those datasets . These tools are then used to create reports, dashboards and data visualizations to make the results of the analyzes available to decision-makers.
The amount of raw data in BI can sometimes seem overwhelming. Especially if they are not represented in a context that justifies their use . They are then no longer worth anything and can even lead to mistakes. In order to have a clear and orderly overview of this information, it is necessary to store it in a dashboard. This aims to make all this raw data accessible and understandable.
They are displayed in the form of tables or graphs which provide a hierarchy. Thus, decision-making becomes faster and more efficient . Fortunately, there are tutorials that go into detail on how to make a dashboard . They guide you step by step through the implementation of this valuable tool and allow you to meet the needs that you have established. The dashboard is therefore essential in supporting BI.
Sporadic use of the term Business Intelligence dates back to the 1860s. However, consultant Howard Dresner is considered to be the first to use the term to refer to the use of data analysis techniques for the benefit of business decision making. , in 1989 . BI technologies are older, however. From time to time, the term business intelligence is replaced by that of business analytics, which more generally refers to advanced analytical technologies but can also include business intelligence.
Business Intelligence: what are the benefits for companies?
Business intelligence programs can have many benefits for the business. They make it possible to accelerate and improve decision-making, optimize internal processes, increase operating efficiency, generate new revenues, and gain the advantage over the competition . BI systems also help businesses identify market trends and spot issues that need to be addressed.
The data business intelligence can include historical information, but also new data from source systems, collected as soon as they are generated . Thus, BI analyzes make it possible to make both tactical and strategic decisions.
Initially, BI tools were primarily used by data analysts and IT professionals who were responsible for analyzing data and producing reports. However, today more and more executives and employees are using BI software themselves, especially with the rise of BI self-service and data discovery tools.
Business Intelligence: what are the business intelligence tools?
The Business Intelligence collects extensive data analysis applications, reporting, online analytical processing (OLAP), mobile BI, BI real-time operating BI of software as a service (SaaS) , and open source BI .
BI technologies also include data visualization software for drawing charts and other infographics, or tools for creating dashboards and scorecards to display the visualized data as performance indicators and metrics. 'business. These apps can be purchased separately from different vendors or as a unified platform from a single vendor.
The IB programs also incorporate forms of advanced analytics such as data mining, predictive analytics , text drilling, statistical analysis or Big Data analysis . In most cases, however, advanced analytical projects are carried out by separate teams of data scientists, statisticians, predictive modelers, or other experienced professional analysts. BI teams usually take on simpler projects.
Business Intelligence or business intelligence: what is the decision chain?
The decision-making chain is the information processing chain making it possible to transform the data collected into information that can be used for decision-making purposes. This chain is made up of elements and tools that are often presented in four distinct categories. Each of these categories corresponds to a phase of the process.
The first step in the decision-making chain is that of data collection . This involves extracting data from the various sources of the company (production systems), transforming them, and uploading them to the database. This is called the "ETL" process (Extract, Transform, Load), which allows data to be adapted for decision-making use.
The second step is that of data storage , or data modeling. It is about centralizing structured and processed data so that they are available for decision-making use, easy to analyze. To do this, we store the data in a Data Warehouse or a Data Mart: a specialized database suitable for decision-making queries.
The third step is that of the distribution or restitution of the data . It consists of using different tools in order to restore information in a form that can be used for decision-making. We will in particular use reporting tools, access portals to dashboards, navigation tools in cubes, or statistical tools. Decision-making portals such as the EIP Enterprise Information Portal also make it possible to distribute information to all partners.
The fourth and last step in the decision-making chain is that of data exploitation . Cleaned, consolidated, accessed and stored data is now ready for analysis by end users or analysts. To do this, we use different tools such as OLAP cubes (for multidimensional analyzes), Data Mining (to look for correlations), or even dashboards presenting key indicators.
Business Intelligence: which personnel and which infrastructures to benefit from BI?
Typically, Business Intelligence data is stored in data warehouses, or in smaller data marts. Additionally, Hadoop systems are increasingly used within BI architectures as data repositories, especially for unstructured data, log files, sensor data, and other types of big data .
Before being used for BI applications, raw data from different source systems must be integrated, consolidated and cleansed using data quality data integration tools to ensure that users analyze accurate data and are consistent.
In addition to BI managers, business intelligence teams typically include BI architects, BI developers, business analysts, and data management professionals . Business users also join the teams to represent the business side and ensure that the needs of the firm are reflected in the BI development process.
Thus, a growing number of companies are replacing traditional development with an approach based on Agile BI and data warehousing using Agile software development techniques to break up BI projects into small parts and offer new functionalities to end users. . This approach allows companies to deploy BI functionality more quickly to refine or modify development plans as business changes or new needs emerge and become priorities.
Business Intelligence: What Are the Potential Problems of Business Intelligence?
One of the main barriers to adopting Business Intelligence is the cultural resistance of company employees . Likewise, poor data quality or a large amount of unnecessary data can be a problem. The solution to getting relevant data from business intelligence systems is standard data. Indeed, data is the main component of any BI solution. These are the building blocks of insights. Businesses need to make sure their data warehouses are tidy before they start extracting insights. Otherwise, they will operate on falsified information.
BI tools themselves can also be obstacles. The tools are more intuitive than before, but are not yet fully accessible . Finally, many companies do not understand their business processes well enough to determine how to improve them. In addition, companies must remain cautious about the processes they choose.
If the process does not have a direct impact on the company's income or if it is not standardized across the company, all efforts may be in vain . Firms need to understand all of the process-related activities, how information and data flow passes through the business, how data is transmitted to different business users, and how it is used by each to fulfill their part of the process. This is the role partly played by the Business Intelligence Manager.
Business Intelligence: the best courses and training in business intelligence
There are a large number of training courses in France that allow you to become an expert in Business Intelligence . These training courses lead to the professions of Data Scientist, Data Miner, project manager in business intelligence, expert consultant in business intelligence or even engineer in business intelligence.
Among these different courses, the best courses are Masters at Bac + 5 level . The most renowned are the Specialized Master in Business Intelligence from EISTI , the Master in Statistical and Financial Engineering from the University Panthéon-Assas Paris II , and the Master (1 and 2) Econometrics, Statistics - Course in Applied Econometrics and Statistics (ESA ) from the University of Orleans .
We can also cite the Master in Computer Science of Data and Decision Making from the Galilée Institute - University of Paris 13 , the Master MIAGE-IF - Computer Science for Finance from the University of Paris-Dauphine , and the Master MIASHS, Statistics Engineering course from the University of Versailles Saint-Quentin-en-Yvelines .
Other universities also offer Masters in Business Intelligence. This is the case of IMT Atlantique, François Rabelais Tours University, Lumière Lyon 2 University, and IAE Montpellier. Note that several organizations offer BI training, such as Cnam, M2i Formation and Orsys Formation .
You can also train yourself by learning to master the tools most used in the field of Business Intelligence such as Qlikview, QlikSense, SSIS, Talend and SQL .
Business Intelligence vs Big Data: What's the Difference?
Big Data can be considered as a component of Business Intelligence , since it allows the company to gather information beyond its own internal sources. Very often, Big Data constitutes the information leading to the “insights” of Business Intelligence.
The notion of Business Intelligence encompasses a wide variety of data, including large online databases that can be considered Big Data. In contrast, the term Big Data refers only to these large data sets .
Big Data and Business Intelligence tools also differ. BI software makes it possible to process standard data sources, but is not suitable for managing Big Data . It is necessary to turn to specialized systems for processing Big Data.
Likewise, the notion of Business Intelligence covers all business processes and data analysis procedures facilitating the collection of Big Data. It therefore also encompasses Data Mining , which can be considered as a form of business intelligence .
More specifically, Data Mining can be considered as a Business Intelligence function . It is used to collect relevant information and generate insights. Business Intelligence can also be thought of as the result of Data Mining, since it consists of using data to acquire insights.
Data Mining makes it possible to search for relevant data sets, while Business Intelligence makes it possible to obtain insights . So, analysts use Data Mining to find the information they need, and use Business Intelligence to determine why it is important.
What are the differences between Business Intelligence and Data Science?
Business Intelligence is a set of technologies, applications and processes used for the analysis of business data. It converts raw data into relevant information , which can be used to guide decision-making.
Data Science, on the other hand, consists of extracting information and knowledge from data using different scientific methods, algorithms and processes . It is therefore a combination of various mathematical tools, algorithms, statistics and machine learning techniques to find historical trends hidden in the data to understand current and future trends.
These two areas are therefore similar, but also present notable differences . Data Science uses statistical and mathematical tools to uncover trends in data, while Business Intelligence is a collection of technologies, applications and processes used by companies for the analysis of business data.
The Data Science focuses on the future of BI on the past and present . Data science makes it possible to deal with both structured and unstructured data, while business intelligence mainly focuses on structured data.
In addition, Data Science is much more flexible than BI, which requires planning and delimiting data sources. The method is scientific in the first case, analytical in the second case.
Data Science is also more complex , and requires the expertise of a Data Scientist whereas Business Intelligence is available to "business users". Finally, the tools used are not the same.