Business Intelligence Solutions Company – All businesses operate on data: information generated from many sources inside and outside of your company. And these data feeds serve as a pair of eyes for executives, providing them with analytical insights into what’s happening with the business and the market. Consequently, any misconception, inaccuracy or lack of information can lead to a distorted view of the market situation, as well as internal operations, followed by bad decisions.
Making data-driven decisions requires a 360° view of all aspects of your business, even those you didn’t think of. But how do you turn unstructured chunks of data into something useful? The answer is business intelligence.
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We have already discussed the machine learning strategy. In this article, we’ll take a look at the actual steps to bring business intelligence into your existing corporate infrastructure. You will learn how to set up a business intelligence strategy and integrate tools into your company’s workflow.
What Is Business Analytics And Why You Need It For Success
Let’s start with a definition: Business intelligence, or BI, is a set of practices for collecting, structuring, analyzing, and turning raw data into actionable business insights. BI considers methods and tools that transform unstructured data sets, compiling them into easy-to-understand reports or dashboards. The primary goal of BI is to provide actionable business insights and support data-driven decision making.
Most of the BI implementation is the use of actual tools that do the data processing. Different tools and technologies form a business intelligence infrastructure. Most often, the infrastructure includes the following technologies that cover data storage, processing, and reporting:
Business intelligence is a technology-driven process that relies heavily on input. The technologies used in BI to transform unstructured or semi-structured data can also be used for data mining, as well as being front-end tools for working with big data.
. This type of data processing is also called descriptive analysis. With the help of descriptive analysis, companies can study the market conditions of their industry, as well as their internal processes. Historical data overview helps to find a company’s pain points and opportunities.
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Based on processing data from past events. Instead of producing summaries of historical events, predictive analytics makes forecasts about future business trends. Those predictions are based on analysis of past events. Therefore, both BI and predictive analytics can use the same techniques to process data. To some extent, predictive analytics can be considered the next stage of business intelligence. Learn more in our article on analytics maturity models.
Prescriptive analytics is the third type that aims to find solutions to business problems and suggests the actions to solve them. Currently, prescriptive analytics is available through advanced BI tools, but the entire area has yet to be developed to a reliable level.
This is the point, when we start talking about the actual integration of BI tools in your organization. The entire process can be broken down into the introduction of business intelligence as a concept to your company’s employees and the actual integration of tools and applications. In the following sections, we’ll take a look at the key points of integrating BI into your business and cover some pitfalls.
Let’s start with the basics. To start using business intelligence in your organization, first and foremost, explain what BI means to all stakeholders. Depending on the size of your organization, the term frames may vary. Mutual understanding is vital here because employees from various 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 purpose of this phase is to introduce the concept of BI to the key people who will be involved in data management. You’ll need to define the actual problem you want to work on, establish KPIs, and organize the specialists needed to launch your business intelligence initiative.
It is important to mention that at this stage, technically, you will make assumptions about the data sources and the standards in place to control the flow of data. You will be able to verify your assumptions and specify your data workflow in later stages. That’s why you need to be ready to change your data sourcing channels and team lineup.
The first big step after aligning the vision would be to define what problem or group of problems you are going to solve with the help of business intelligence. Setting goals will help you determine other high-level metrics for BI, such as:
Along with goals, at that stage, you’ll need to think about possible KPIs and evaluation metrics to see how the task is accomplished. They can be financial constraints (budget applied to development) or performance indicators such as query speed or report error rate.
Why Does My Company Need Business Inteligence?
By the end of this stage, you should be able to set up the initial requirements of the future product. It can be a list of features in a product portfolio consisting of user stories or a more simplified version of this requirements document. The main point here is that based on the requirements, you need to be able to understand what kind of architecture, features and capabilities you want from your BI software/hardware.
Compiling a requirements document for your business intelligence system is a key point in understanding which tool you need. For large companies, creating your own custom BI ecosystem may be considered for a number of reasons:
For smaller companies, the BI marketplace offers a large number of tools that are available in both integrated versions and cloud-based technologies (Software-as-a-Service). It is possible to find offerings that cover almost any type of industry-specific data analysis with flexible possibilities.
Based on the requirements, type of industry, size and needs of your business, you will be able to understand if you are ready to invest in a custom BI tool. Otherwise, you can choose a provider that will carry the implementation and integration burden for you.
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The next step would be to bring together a group of people from different departments in your company to work on your business intelligence strategy. Why would you even need to create such a group? The answer is simple. The BI team helps bring together representatives from different departments to streamline communication and obtain department-specific information about required data and its sources. Therefore, your BI team lineup should include two main categories of people:
These individuals will be responsible for providing the team with access to the data sources. They will also contribute their domain knowledge to choose and interpret different types of data. For example, a marketer might define whether their website traffic, bounce rate, or newsletter signup numbers are valuable data types. While your sales rep can provide insights into meaningful customer interactions. On top of that, you will be able to access marketing or sales information through a single person.
The second category of people you want on your team are BI-specific members who will lead the development process and make architectural, technical, and strategic decisions. Therefore, as a required standard, you will need to determine the following roles:
BI Manager. This person should be armed with theoretical, practical and technical knowledge to support the implementation of your actual strategy and tools. You may be an executive with knowledge of business intelligence and access to data sources. The Head of BI is a person who will make decisions to drive the implementation.
Business Intelligence: A Complete Overview
The BI engineer is a technical member of your team who specializes in building, implementing, and configuring BI systems. BI engineers typically have experience in software development and database configuration. They must also be well versed in data integration methods and techniques. A BI engineer can lead your IT department in implementing your BI toolset. Learn more about data professionals and their roles in our dedicated article.
The data analyst must also become part of the BI team to provide the team with expertise in data validation, processing, and visualization.
Once you have a team and have considered the data sources required for your specific problem, you can start developing a BI strategy. She can document her strategy using traditional strategy documents, such as a product roadmap. The business intelligence strategy can include various components depending on the industry, company size, competition, and business model. However, the recommended components are:
This is the documentation for the chosen data source channels. These should include any type of channel, whether it be a stakeholder, general industry analysis, or input from your employees and departments. Examples of such channels can be Google Analytics, CRM, ERP, etc.
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Documenting your industry-standard KPIs, as well as specific ones, can open up the most complete picture of your business’ growth and losses. Ultimately, BI tools are built to track these KPIs by supporting them with additional data.
At this stage, define what type of reports you need to conveniently extract valuable information. In the case of a custom BI system, you might consider visual or textual representations. If you’ve already chosen your provider, you may be limited in terms of reporting standards, as providers set their own. This section may also include data types that you want to deal with.
An end user is a person who will view the data through the reporting tool interface. Depending on the end users, you may also consider a report
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