Single-user User Interface Business Intelligence Tools Free Of Charge

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Single-user User Interface Business Intelligence Tools Free Of Charge – All businesses operate using data – information generated from many sources both internal and external to your company. These channels of data act as a pair of eyes for executives, providing them with analytical information about what is going on in the business and the market. Accordingly, any misunderstanding, inaccuracy or lack of information may 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-degree view of all aspects of your business, even those you haven’t considered. But how do you turn the unstructured bits of data into something useful? The answer is business intelligence.

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We have already discussed machine learning strategy. In this article, we will discuss the actual steps of introducing business intelligence into your company’s existing infrastructure. You will learn how to set up a business intelligence strategy and integrate the tools into your company’s workflow.

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Let’s start with a definition: business intelligence or business intelligence is a set of practices for collecting raw data, structuring it, analyzing it, and turning it into actionable business insights. BI takes into account the methods and tools that transform unstructured datasets, and compiles them into easy-to-understand reports or dashboards. The main purpose of business intelligence is to provide actionable business insights and support data-driven decision making.

The bulk of implementing business intelligence is using the actual tools that process the data. Various tools and technologies form a business intelligence infrastructure. Most often, the infrastructure includes the following technologies covering 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 analytics. With the help of descriptive analytics, companies can study market conditions in their industry, as well as their internal operations. Overview of historical data helps find weaknesses and opportunities for a business.

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Based on the processing of past event data. Rather than producing overviews of historical events, predictive analysis makes predictions about future business trends. These predictions are based on an analysis of past events. Therefore, both intelligence and predictive analysis can use the same methods to process data. To some extent, predictive analytics can be considered the next stage of business intelligence. Read more in our article about analytics maturity models.

Descriptive analytics is the third type that aims to find solutions to business problems and suggest actions to solve them. Prescriptive analytics is currently available via advanced business intelligence tools, but the whole area has not evolved to a reliable level yet.

So that’s the point, when we start talking about the actual integration of business intelligence tools into your organization. The whole process can be divided 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 walk you through the key points of integrating business intelligence into your company and cover some of the pitfalls.

Let’s start with the basics. To start using Business Intelligence in your organization, first and foremost explain the meaning of Business Intelligence with all stakeholders. Depending on the size of your organization, term frames may vary. Mutual understanding is vital 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 analysis.

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The other purpose of this stage is to introduce the concept of business intelligence to the key people who will be involved in data management. You will have to define the actual problem you want to work on, set KPIs, and organize the specialists required to launch your business intelligence initiative.

It is important to note that at this point, the technologist will be making assumptions about the data sources and standards set to control the flow of data. You will be able to validate your assumptions and define the data workflow in the later stages. That’s why you need to be prepared to change your data source channels and lineup.

The first big step after aligning the vision is to define the problem or set of problems that you will solve with the help of business intelligence. Goal setting will help you define more high-level business intelligence parameters such as:

Besides the objectives, at that point you will have to think about possible KPIs and evaluation metrics to see how the task will be accomplished. These can be financial constraints (the budget applied to development) or performance indicators such as query speed or report error rate.

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By the end of this stage, you should be able to form the preliminary requirements for the future product. This could be a list of features in a product backlog made up of user stories, or a more streamlined version of this requirements document. The key point here is that depending on the requirements, you should be able to understand what kind of architecture, features and capabilities you want from your business intelligence software/hardware.

Compiling a requirements document for a business intelligence system is a key point in understanding the tool you need. For large companies, consideration can be given to building their own custom environmental ecosystem for several reasons:

For smaller companies, the business intelligence market offers a large number of tools that are available as both embedded versions and cloud-based (Software-as-a-Service) technologies. It is possible to find offerings that cover almost any type of industry-specific data analysis with flexible capabilities.

Depending on the requirements, the type of industry, the size and needs of your business, you will be able to understand if you are ready to invest in a customized business intelligence tool. Otherwise, you can choose a vendor that will take the burden of implementation and integration for you.

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The next step will be to gather a group of people from different departments of 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 simplify communication and gain department-specific insights into the required data and its sources. Therefore, the lineup of your business intelligence team should include two main categories of people:

These people will be responsible for providing the team with access to the data sources. They will also contribute their knowledge of the field to the selection and interpretation of different types of data. For example, a marketing professional can determine whether your website traffic, bounce rate, or newsletter sign-up numbers are valuable data types. While your salesperson can provide insights into meaningful interactions with customers. Moreover, you will be able to access marketing or sales information via a single person.

The second category of people you want on your team are BI-defined members who will lead the development process and make architectural, technology and strategic decisions. Therefore, as a required criterion, you will need to define the following roles:

BI head. This person should be armed with theoretical, practical and technical knowledge to support the implementation of your strategy and actual tools. This could be an executive with knowledge of business intelligence and access to data sources. The Chief Business Intelligence Officer is the person who makes decisions to drive execution.

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A BI Engineer is a technical member of your team who specializes in building, implementing and setting up business intelligence systems. BI engineers usually have a background in software development and database configuration. They should also be well versed in data integration methods and techniques. The Business Intelligence Engineer may lead the IT department in implementing the Business Intelligence toolkit. Learn more about Data Professionals and their roles in our dedicated article.

The data analyst should also become part of the BI team providing the team with expertise in data validation, manipulation and data visualization.

Once you have a team and have thought about the data sources required for your specific problem, you can start developing a business intelligence strategy. You can document your strategy using traditional strategy documents such as a product roadmap. A business intelligence strategy may include different components depending on your industry, company size, competition, and business model. However, the recommended ingredients are:

This is the documentation of your chosen data source channels. These should include any type of channel, be it from stakeholders, industry analytics in general, or information from your employees and departments. Examples of these channels are Google Analytics, CRM, ERP, etc.

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Documenting your industry standard KPIs as well as your own KPIs can open up the full picture of your business growth and losses. Ultimately, business intelligence tools are built to track these KPIs and back them up with additional data.

At this point, decide what type of reports you need to extract valuable information easily. In the case of a dedicated business intelligence system, you can consider visual or textual representations. If you have already selected the supplier, you may be limited in terms of reporting standards, as vendors set their own standards. This section may also include the types of data you want to work with.

The end user is the person who will monitor the data through the reporting tool interface. Depending on the end users, you may also consider reporting

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