Business Intelligence Deutsch – It’s critical for businesses to have a clear view of all their data to stay competitive, which is where business intelligence (BI) tools come in. In fact, about 50% of all businesses use BI tools now, and projections show continued growth in the coming years.
But for those new to the tool or just looking to learn more, BI can be difficult to understand in detail. We’ve created this comprehensive guide to educate people about what BI is, how it works, and more.
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Business Intelligence combines business analytics, data mining, data visualization, data tools and infrastructure, and best practices to help organizations make data-driven decisions. In practice, you know you have modern business intelligence when you have a comprehensive view of your organization’s data and use that data to drive change, eliminate inefficiencies, and quickly adjust to marketing or supply changes. Today’s BI solutions prioritize dynamic analytics for automation, managed data on trusted platforms, empowered business users, and speed of insight.
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It’s important to note that this is the current definition of BI – and BI has a history of being suppressed as a buzzword. Traditional business intelligence, caps and all, originally emerged in the 1960s as a system for sharing information across organizations. The term business intelligence was coined in 1989 with computer models for decision making. These applications were further developed and transformed data into insight before becoming a specific offering from BI teams with IT service solutions. This article serves as an introduction to BI and is the tip of the iceberg.
Businesses and organizations have questions and goals. To answer these questions and track performance against these goals, they collect the necessary data, analyze it, and determine what actions they need to take to achieve their goals.
On the technical side, raw data is collected from business processes. The data is processed and then stored in data warehouses, cloud, applications and files. Once stored, users can access the data and begin the analysis process to answer business questions.
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BI platforms also provide data visualization tools that transform data into charts or graphs that are also presented to any key stakeholder or decision maker.
More than a specific “thing”, business intelligence is a general term that includes processes and methods for collecting, storing and analyzing data from business operations or operations to improve performance. All of these things come together to create a holistic view of the business to help people make better, actionable decisions. Over the past few years, business intelligence has evolved to include many processes and functions to help improve performance. These programs include:
Business intelligence includes data analysis and business analysis, but it is used only as part of the overall process. BI helps users get results from data analysis. Data scientists delve into data using advanced statistics and predictive analytics to discover patterns and predict future patterns.
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Data analysis asks: “Why did this happen and what will happen in the future?” Business intelligence takes those models and algorithms and parses the results into actionable language. According to Gartner’s IT Glossary, “Business analytics includes data analysis, predictive analytics, applied analytics, and analytics.” In short, organizations perform business analytics as part of their larger business intelligence strategy.
BI is designed to answer specific questions and provide analytical insights for decision making or planning. However, companies can use analytics programs to continuously improve tracking and repeat queries. Business analysis should not be a linear process because the answer to one question can lead to subsequent and repeated questions. Instead, think of the process as a cycle of access, discovery, discovery, and sharing of information. This is called the analytics cycle, a modern term that describes how businesses use analytics to respond to changing questions and expectations.
Historically, business intelligence tools were based on the traditional business intelligence model. It was a top-down approach where business intelligence was driven by the IT organization and most, if not all, analytical questions were answered through static reports. This means that if someone has a follow-up question about the feedback they received, their request goes down the feedback queue and they have to start the process all over again. This led to slow and tedious feedback cycles, and people couldn’t use current data to make decisions.
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Traditional business intelligence is still a common way of reporting regularly and answering static questions. However, today’s business intelligence is interactive and accessible. While IT departments are still an important part of managing data access, many levels of users can customize dashboards and generate reports quickly. With the right software, users have the ability to visualize data and answer their questions.
So now you know what BI is and how it works. But how does BI help businesses?
BI is more than just software – it’s a way to keep a real-time overview of all your relevant business data. Implementing BI provides countless benefits, from better analytics to increased competitive advantage. Some of the most important benefits of business intelligence are:
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Many different industries, including healthcare, IT, and education, have adopted business BI ahead of the curve. All organizations can use data to transform operations. With so much information in this article and available online, it can be difficult to fully understand the potential of BI. Real world examples can help, which is why we create lessons from our clients’ success stories.
For example, financial services company Charles Schwab used business intelligence to take a comprehensive view of all of its branches across the United States to understand performance metrics and identify areas of opportunity. Access to a centralized business intelligence platform allowed Schwab to put its departmental data into a single view. Branch managers can now identify clients whose investment needs may change. And leadership can track when an area’s performance is above or below average and click on it to see which departments are driving that area’s performance. This leads to more opportunities for improvement and better customer service for customers.
Another example is meal kit service HelloFresh, which automates its reporting processes because its digital marketing team spends a lot of time on it each month. With the help of HelloFresh, it saved the team 10-20 hours of work per day and allowed them to create targeted marketing campaigns and segments.
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A BI strategy is your blueprint for success. You need to decide how the data will be used, gather key roles, and define responsibilities early on. It may seem simple on the surface. However, starting with business goals is the key to your success.
There are three main types of BI analytics that cover different needs and applications. These are predictive analysis, descriptive analysis, and deterministic analysis.
Predictive analytics takes historical and real-time data and models future results for planning purposes. Descriptive analysis is the process of identifying trends and relationships in data using historical and current data. And structured analytics takes all the relevant data to answer the question, “What should my business do?”
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We have covered most of the good points of BI. But like any big business decision, implementing BI comes with its pitfalls and failures, especially during the implementation phase.
Many automated business intelligence tools and platforms simplify the analysis process. This makes it easy for people without technical knowledge in data mining to see and understand their data. Many BI platforms are available for ad-hoc reporting, data visualization, and creating dashboards tailored to different levels of users. We’ve outlined our recommendations for evaluating today’s BI platforms so you can choose the right platform for your organization. One of the most common ways to provide business intelligence is through data visualization.
The key to successfully implementing BI is choosing the right platform for the job. When choosing your equipment, it’s best to keep in mind which features are most useful for your business. Some of the key features of BI tools are:
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Undoubtedly one of the most useful BI tools is dashboards, which allow complex data to be collected and viewed all in one place. These dashboards can serve a variety of purposes, such as sophisticated analytics or stakeholder buy-in. The challenge is to create the best dashboard for your needs.
As the data environment grows and the collection, storage and analysis of data becomes more complex, it is important to consider the relationship between BI and big data. Big data has been the buzzword in business recently, so what exactly is it? Well, data experts describe it with the “Four Vs”: Volume, Velocity, Value and Range. These four define big data and differentiate them. In particular, volume is something that people often refer to as a key factor, because the amount of data is constantly growing and it is easy to store it for a long time.
As you can imagine, this is important for BI, as businesses generate more data every year and BI platforms need to keep up with the growing demands placed on them. A good platform will grow
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