Totally Complimentary Business Intelligence Tool – All businesses use data to operate – information from multiple sources outside of your company. And these data channels serve as a pair of eyes for the leaders, providing them with analytical information about what is happening in the business and the market. As a result, any wrong, incorrect, or uninformed assumptions can lead to a distorted view of market conditions and performance – resulting in bad decisions.
Making data-driven decisions requires a 360° view of all aspects of your business, even those you don’t expect. But how do you turn a chunk of data into something useful? The answer is business intelligence.
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We have already discussed machine learning techniques. In this article, we will discuss the process of introducing business intelligence into your existing enterprise infrastructure. You will learn how to establish a business intelligence strategy and integrate the tool into your company’s workflow.
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Let’s start with a definition: business intelligence or BI is the practice of collecting, organizing, analyzing and converting raw data into actionable business insights. BI considers methods and tools that transform unstructured data, aggregating them into easy-to-understand reports or bulletin boards. The primary purpose of BI is to provide actionable business insights and support data-driven decisions.
The biggest part of implementing BI is using the actual tools to do the data processing. Different tools and technologies form the business intelligence infrastructure. Often, infrastructure includes the following technologies that cover security, processing and reporting:
Business intelligence is a technology-driven process that is based on input. The technology used in BI to transform unstructured or semi-structured data can be used for data entry, as well as being a front-end tool to work with big data.
. This type of data processing is also called descriptive analysis. With the help of analytics, businesses can learn about the market conditions of their companies, as well as their internal processes. Historical data collection helps to identify the pain points and opportunities of the business.
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Based on the data structure of previous events. Rather than creating an explanation of historical events, predictive analytics predicts future business trends. The predictions are based on analysis of past events. So, both BI and predictive analytics can use the same process to process data. To some extent, predictive analytics can be considered as another level of business intelligence. Read more in our article about the eligibility criteria of the survey.
Analytical analysis is a third type that seeks to find solutions to business problems and suggests actions to solve them. At the moment, prescriptive analysis is achieved through advanced BI tools, but all areas have not yet developed to a reliable level.
So here is the main point, when we start talking about the integration of BI tools in your organization. The whole process can be broken down into the integration of business intelligence as an idea for your company’s employees and the integration of tools and applications. In the next section, we’ll go over the basics of implementing BI in your company and cover some of the pitfalls.
Let’s start with the basics. To start using business intelligence in your organization, first define the meaning of BI among all your stakeholders. Depending on the nature of your organization, the frame of reference may be different. Understanding relationships is important here because employees of different departments will be involved in data processing. So, make sure everyone is on the same page and don’t confuse business intelligence with predictive analytics.
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Another goal of this course is to explain the concept of BI to the leaders who will be involved in data management. You’ll define the exact problem you want to work on, set KPIs, and organize the experts you need to start your business intelligence strategy.
It is important to explain that at this time, you, and the technology, will think about the source of the data and the set values to control the data flow. You will be able to review your ideas and define your data workflow at the end. That’s why you have to be ready to change the channel of getting data in your group.
The first big step when refining the vision will be to define a problem or a group of problems that you will solve with the help of business intelligence. Setting these goals will help you determine other high-level objectives for BI such as:
Along with these objectives, at that time, you should think about possible KPIs and analytical metrics to see how the work is being done. Those can be financial constraints (expenditure invested in development) or performance indicators such as interview or defect rates.
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By the end of this stage, you will be able to plan the initial requirements of future products. This could be a list of features in the product backlog with a user report, or a simpler form of required documentation. The point here is that, based on these requirements, you should be able to understand what kind of architecture, features, and capabilities you need from your BI software/hardware.
Gathering the documentation required for your business intelligence process is key to understanding the tools you need. For large businesses, building their own BI environment can be considered for several reasons:
For small companies, the BI market offers a large number of tools available both as integrated models and cloud-based technologies (Software-as-a-Service). It is possible to find offers that cover almost any type of data analysis that any company can make a difference.
Depending on the requirements, your company’s type, size, and business needs, you will be able to understand whether you are ready to invest in a custom BI application. Otherwise, you can choose a vendor who will carry the implementation and installation burden for you.
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The next step would be to bring together a team of people from different departments of your company to work on your business intelligence strategy. Why would you want to create such a group? The answer is simple. BI teams help bring together representatives from different departments to facilitate communication and gain a departmental understanding of the data needed and its source. So, your BI membership lineup should include two types of people:
These individuals will be responsible for providing the group with access to the data source. They will also contribute to their domain knowledge in selecting and interpreting different types of data. For example, a marketing expert can explain whether your website traffic, bounce rate, or newsletter subscription numbers are valuable types of data. Although your marketing manager can provide insight and valuable relationships with customers. On top of that, you will be able to receive sales or marketing information from one person.
The second type of people you want in your team are BI team members who will lead the development process and make organizational, technical and strategic decisions. So, according to the required standard, you will need to determine the following functions:
Chapter of BI. This person must use the knowledge, practical, and technical skills to support the implementation of your plans and actual tools. This can be an executive with knowledge of business intelligence and access to data sources. The head of BI is the one who has to make decisions to improve the implementation of the law.
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A BI engineer is a technical member of your team who specializes in building, implementing and setting up BI systems. Oftentimes, BI engineers have a software development and data processing background. They must be well versed in data entry processes and procedures. A BI engineer can lead your IT department in implementing your BI tools. Learn more about data professionals and their work in our dedicated article.
The data analyst should also be part of the BI team to provide the team with expertise in data validation, processing, and data visualization.
Once you have a team and you’ve considered the data sources needed for your specific problem, you can start creating a BI strategy. You can document your strategy using a traditional strategy paper such as a product roadmap. A business intelligence strategy can include different components depending on your company, your company’s size, competition, and your business model. However, the recommended resources are:
This is a document of your chosen data source channel. These should include any type of channel, whether it’s a manager, general company reviews, or information from employees in your department. Examples of such channels can be Google Analytics, CRM, ERP, etc.
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Recording your company’s standard KPIs as well as your own can unlock a more complete picture of your business’s growth and losses. Finally, BI tools are developed to track these KPIs and support them with other data.
At this point, define the type of report you need to effectively deliver useful information. In terms of traditional BI systems, you can consider visual or textual presentations. If you have already chosen a dealer, you may have limitations in terms of reporting standards, as the dealers set their own. This section can also include the type of data you want to interact with.
The end user is the person who will see the data through the interface of the reporting device. Depending on the end users, you may also consider reporting
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