Business intelligence (BI) is the process of transforming raw data into actionable insights that may help guide the strategic and operational business choices of a company. BI makes use of both software and services. The goal of business intelligence (BI) solutions is to give users with in-depth insight about the condition of the company by accessing and analyzing data sets and presenting the results of analytical processes in the form of reports, summaries, dashboards, graphs, charts, and maps.
The phrase "business intelligence" is often used to refer to a variety of technologies that provide rapid and simple access to insights about the present status of a company, which are derived from the data that is accessible.
How It Can Look Like
The dashboard is likely the most emblematic example of a business intelligence (BI) tool, and reporting is one of the most important aspects of business intelligence. Hosted software programs known as dashboards are capable of automatically compiling all of the data that is currently accessible into charts and graphs that provide an overview of the current situation at the firm.
Business intelligence does not tell business users what to do or what will happen if they take a certain course of action; however, business intelligence is also not solely about generating reports. Business intelligence can tell business users what will happen if they take a certain course of action. Rather, business intelligence (BI) makes it possible for individuals to analyze data in order to see patterns and generate insights by simplifying the processes of finding, merging, and querying the information that is required to make intelligent business choices.
According to Chris Hagans, vice president of operations for WCI Consulting, a consultancy that focuses on BI, a company that wants to better manage its supply chain needs BI capabilities to determine where delays are happening and where variabilities exist within the shipping process. For example, a company that wants to better manage its supply chain needs to determine where delays are happening and where variabilities exist within the shipping process. This firm could also utilize its BI skills to find out which items have the highest incidence of being delayed as well as which forms of transportation have the highest incidence of being engaged in delays.
According to Cindi Howson, research vice president at Gartner, an IT research and consultancy organization, the possible use cases for business intelligence go beyond the conventional business success measures of increased sales and decreased expenses. She cites as an example the school system in Columbus, Ohio, and its effectiveness in improving student learning and high school graduation rates by employing business intelligence (BI) tools to assess multiple data points, ranging from student attendance rates to student performance.
Tableau and G2 are two manufacturers of business intelligence software that also provide tangible examples of how firms should use business intelligence solutions.
Business intelligence (BI) might be used by a cooperative organization to keep track of member recruitment and retention.
Using CRM data, business intelligence systems might automatically create sales and delivery reports.
BI might be used by a sales team to build a dashboard that would display where each sales rep's prospects are located on the sales funnel.
Business Intelligence vs. Business Analytics
You probably noticed one thing about those examples, and that is that they give insights into the present health of the company or organization. For instance, they provide information about where sales prospects now stand in the pipeline. How many members did we lose this month, and how many did we gain? This highlights the most important difference that can be made between business intelligence and another phrase that is closely connected to it: business analytics.
The descriptive nature of business intelligence involves informing users not just of current events but also of the historical events that led up to the current condition of affairs. On the other hand, business analytics is an umbrella term for data analysis techniques that are both predictive — that is, they can tell you what is going to happen in the future — and prescriptive — that is, they can tell you what you should be doing to create better outcomes. In other words, business analytics is an umbrella term for predictive and prescriptive data analysis techniques. (The field of data analytics as a whole is sometimes broken down further into subfields, one of which is known as business analytics due to its emphasis on commercial enterprises.)
The difference between the predictive or descriptive capabilities of business analytics and the descriptive or predictive capabilities of business intelligence extends a little farther than the period that we are focusing on here. It also goes to the core of the issue of who the target audience should be for business information. The Stitchdata blog argues that the primary objective of business intelligence (BI) is to provide company managers with clear pictures of the present state of things. One of the goals of business intelligence is that it should be easy for relatively non-technical end users to understand, and even for them to dive into the data and create new reports. This is in contrast to the fact that the predictions and advice derived from business analytics require data science professionals to analyze and interpret.
The Strategy For Business Intelligence
Historically, IT professionals were the major consumers of business intelligence (BI) solutions. However, business intelligence technologies have progressed to become more understandable and accessible to users, making it possible for a wide number of people working in a range of organizational domains to make use of the tools.
According to Howson of Gartner, there are two distinct forms of BI. The first kind of business intelligence (BI) is known as conventional or classic BI. In this type of BI, IT experts build reports by using data from internal transactions. The second kind is contemporary business intelligence, which allows business users to connect with flexible and user-friendly tools in order to do data analysis in a more timely manner.
Howson notes that firms would often use traditional BI for certain sorts of reporting, such as regulatory or financial reports, where the need of accuracy cannot be overstated and where the queries and data sets utilized are standardized and predictable. When business users require insight into swiftly changing dynamics inside an organization, such as marketing events, where being fast is valued more than having the data just correct, current business intelligence technologies are often what organizations turn to.
Poor data practices, tactical missteps, and other issues may make it difficult for many businesses to adopt successful business intelligence strategies, despite the fact that sound business intelligence is important to the process of making strategic business choices.
Business Analytics Provided On A Self-Service Basis
Self-service business intelligence is a category of business intelligence (BI) tools that is designed to generate reports without the need for intervention from IT personnel. This category of BI tools was created as a result of the push to make it possible for virtually anyone to obtain useful information from business intelligence tools. Self-service business intelligence (BI) solutions provide companies the ability to make it simpler for managers and other employees who are not technically trained to access the company's internal data reports.
Business intelligence dashboards and user interfaces (UIs) that contain pull-down menus and simple drill-down points that enable users to access and alter data in easy-to-understand ways are among the keys to the success of self-service business intelligence (self-service BI). There is no question that a certain degree of training will be necessary; nevertheless, if the benefits of the tools are clear enough, staff will be ready to jump on board with the initiative. (If you're in the market for a self-service business intelligence solution, CIO.com's Martin Heller will guide you through the decision-making process and compare and contrast his top five recommendations.)
Bear in mind, however, that self-service business intelligence comes with its own share of potential dangers. When you encourage your business users to take on the role of ad hoc data engineers, you run the risk of ending up with a disorganized mix of metrics that differ across departments, encountering issues with data security, and even racking up significant licensing or SaaS bills if there is no centralized control over the rollout of the tools. Therefore, even if you have decided to implement self-service business intelligence inside your company, you cannot just purchase a product off the shelf, direct your employees to the user interface (UI), and hope for the best results.
Software And Computer Systems For Business Intelligence
The term "business intelligence" refers to a broad category that encompasses a wide range of tool categories. The following are some of the most essential software categories and functionalities, as broken down by the software selection service SelectHub:
The acronym ETL stands for "extract-transfer-load" and refers to the tools that are used to import data from one data store into another.
OLAP (online analytical processing)
According to SelectHub, the dashboards and visualization are by far the most popular of these tools. This is because they provide concise and easy-to-understand data summaries, which are at the core of the value proposition for business intelligence.
The business intelligence (BI) market is saturated with a huge number of suppliers and products, making it difficult to choose which one to use. The following are some of the most important players:
Tableau is a self-service analytics platform that can interact with a variety of data sources and delivers data visualization. Some of these data sources include Excel and Microsoft Azure SQL Data Warehouse.
Splunk is a "directed analytics platform" that can provide business information and data analytics on an enterprise level.
Alteryx, which integrates analytics derived from a variety of sources in order to ease processes and give an abundance of business intelligence insights,
Qlik, which is based on data visualization, business intelligence, and analytics, offers a broad and scalable business intelligence platform.
Domo is a cloud-based platform that provides business intelligence solutions that are specialized for a variety of roles and sectors (including educational institutions, health care providers, manufacturers, and financial services) (including CEOs, sales, BI professionals and IT workers)
Dundas BI is mostly used for the creation of scorecards and dashboards, but it is also capable of doing both conventional and ad-hoc reporting.
In place of the tried-and-true Google Analytics platform is the new and improved Google Data Studio.
Einstein Analytics is Salesforce.com's effort to enhance business intelligence (BI) by using AI Birst, which is a cloud-based service in which several instances of BI software share a similar data backend. Salesforce.com developed Einstein Analytics.
Analyst In Charge Of Business Intelligence
Business intelligence analysts are a must for the workforce of any organization that takes business intelligence (BI) seriously. An in-depth article on the responsibilities of that job can be found on CIO.com; in general, they aim to use all of the features of BI tools to get the data that companies need; the most important of these responsibilities is discovering areas of revenue loss and identifying where improvements can be made to save the company money or increase profits.
Even if your firm depends on self-service BI tools on a day-to-day basis, business intelligence analysts still have a vital role to play. This is because business intelligence analysts are required for the management and maintenance of self-service BI products and the vendors that provide them. In addition to this, they will organize and standardize the reports that managers will be creating in order to guarantee that the outcomes will be comparable and relevant across your whole firm. In addition, in order to prevent issues known as "garbage in, garbage out," business intelligence analysts have to ensure that the data that is being inputted into the system is accurate and consistent. This sometimes requires extracting the data from other data repositories and cleaning it up.
The Path That Business Intelligence Will Take In The Future
Moving forward, Howson says that Gartner sees a third wave of disruption on the horizon. This wave is something the research firm calls "augmented analytics," in which machine learning is baked into the software and will guide users on their queries into the data. Gartner calls this wave of disruption the "fourth industrial revolution."
She claims that it will use business intelligence and analytics, and that it will be clever.
According to Gorman, the mix of features that are incorporated in these software platforms will result in each function being more powerful on its own and providing greater value to the businessmen who use them.
"Someone will look at reports from, for example, last year's sales — that's business intelligence — but they'll also get predictions about next year's sales — that's business analytics — and then add to that a what-if capability: What would happen if we did X instead of Y," Gorman says, explaining that software makers are moving to develop applications that will provide those functions within a single application rather than delivering them via multiple platforms as is currently the case. This is
"At this time, the algorithm generates suggestions with a greater value. He goes on to say that as a result, the person making the decisions becomes more effective, more powerful, and more accurate.
And although business intelligence will continue to be beneficial in and of itself, according to Howson, firms will be unable to compete if they do not go beyond business intelligence and implement advanced analytics as well.
According to the Magic Quadrant report published by Gartner, businesses that provide their customers with "users access to a curated catalog of internal and external data will realize twice the business value from analytics investments than those that do not," and this is expected to take place by the year 2020.
Howson continues by saying, "There is a need for reporting; nevertheless, reporting by itself is not sufficient." If all you're doing is reporting, you're already falling behind schedule. You are falling behind unless your reporting is both intelligent and agile. You're a laggard."