Apa Itu Business Intelligence – The entire business runs on data – information generated from numerous internal and external sources within your company. And these data channels serve as a pair of eyes for executives, providing them with insight into what’s going on with the business and the market. Consequently, any misunderstanding, inaccuracy or lack of information can lead to a distorted picture of the state of the market as well as the inner workings – followed by bad decisions.
Data-driven decision making requires a 360° view of all aspects of your business, even those you haven’t considered. But how do you turn unstructured chunks of data into something useful? The answer is business intelligence.
Apa Itu Business Intelligence
We have already discussed the machine learning strategy. In this article, we’ll discuss the actual steps required to bring business intelligence into your existing enterprise infrastructure. You will learn how to formulate a business intelligence strategy and integrate the tools into your company’s workflow.
Role Of Business Intelligence In Strategic Business Planning
Let’s start with a definition: business intelligence or BI is a set of practices for collecting, structuring, analyzing and transforming raw data into business intelligence. BI examines methods and tools that transform unstructured data sets, aggregating them into easy-to-understand reports or dashboards of information. The main purpose of BI is to provide actionable business information and support data-driven decision making.
The biggest part of implementing BI is using the actual tools that do the data processing. Different tools and technologies make up the 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 data. The technologies used in BI to transform unstructured or semi-structured data can also be used for data mining, as well as interface tools for working with big data.
Key Benefits Business Intelligence Provides Your Organization
. 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. Viewing historical data helps identify problems and business opportunities.
Based on data processing of past events. Rather than creating an overview of historical events, predictive analytics makes predictions about future business trends. These predictions are based on analysis of past events. Thus, both BI and predictive analytics can use the same data processing techniques. To some extent, predictive analytics can be considered the next phase of business intelligence. Read more in our article on analytical maturity models.
Prescriptive analytics is the third type that aims to find solutions to business problems and suggest actions to solve them. Currently, predefined analytics are available through advanced BI tools, but the entire field is yet to be developed to a reliable level.
Business Intelligence Development: Why It Matters
So this is where we start talking about actually integrating BI tools into your organization. The whole process can be divided into introducing 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 through the basics of integrating BI into your company and cover some of the pitfalls.
Let’s start with the basics. To start using business intelligence in your organization, first of all explain the concept of BI to all your stakeholders. Depending on the size of your organization, timeframes may vary. Mutual understanding is crucial here because employees in 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.
Another purpose of this phase is to introduce the concept of BI to the key people who will be involved in data management. You will need to define the real problem you want to work on, set KPIs and organize the necessary experts to start your business intelligence initiative.
Business Intelligence And The Decision Making Process In Manufacturing
It is important to note that at this stage, technically, you will be making assumptions about the data sources and standards defined to control the data flow. You will be able to test your assumptions and define the data workflow at later stages. That’s why you need to be prepared to change your data source channels and team composition.
The first big step after aligning the vision would be to define the problem or group of problems that you will solve with the help of business intelligence. Setting goals will help you identify further high-level parameters for BI, such as:
Along with the objectives, at this stage you should think of possible KPIs and evaluation metrics to see how the work has been achieved. These can be financial constraints (budget applied to development) or performance metrics such as query speed or report error rate.
An Insight Into Business Intelligence In Ecommerce
By the end of this phase, you should be able to formulate the initial requirements of the future product. This can be a list of features in a product backlog consisting of user stories or a simplified version of this requirements document. The main point here is that based on the requirements, you should be able to understand the type of architecture, features and capabilities you want from your BI software/hardware.
Writing the requirements document for your business intelligence system is a key point in understanding which tool you need. For large enterprises, building their own custom BI ecosystem can be considered for several reasons:
For smaller companies, the BI market offers a large number of tools that are available both as embedded versions and as 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 capabilities.
Business Intelligence: Definisi, Manfaat Dan Contoh Penerapannya
Based on your 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 vendor that will carry the burden of implementation and integration for you.
The next step would be to assemble a team of people from different parts of your company to work on your business intelligence strategy. Why create such a group? The answer is simple. The BI team helps bring together representatives from different departments to streamline communication and gain specific insights into the data needed and its sources. Therefore, your BI team composition should include two main categories of people:
These individuals will be responsible for providing the team with access to data sources. They will also contribute their knowledge in the field of selection and interpretation of different types of data. For example, a marketer can determine whether your website traffic, bounce rate, or newsletter subscription numbers are valuable types of data. While your sales rep can provide insight into meaningful customer interactions. In addition, you will be able to access marketing or sales information through a single person.
How Do Companies Use Business Intelligence?
Another 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 mandatory template, you will need to define the following roles:
Chief BI. This person should be armed with theoretical, practical and technical knowledge to support the implementation of your strategy and real tools. It could be a CEO with business intelligence knowledge and access to data sources. The head of BI is the person who will make the decisions to start the implementation.
A BI engineer is a technical member of your team who specializes in building, implementing and tuning BI systems. Typically, BI engineers have a background in software development and database configuration. They must also be well versed in data integration methods and techniques. A BI engineer can lead the IT department in implementing the BI toolset. Learn more about data scientists and their roles in our dedicated article.
Diy Business Intelligence
A data analyst should also join the BI team to provide the team with expertise in data validation, processing and visualization.
Once you’ve built a team and considered the data sources needed for your specific problem, you can start developing a BI strategy. You can document your strategy using traditional strategy documents, such as a product roadmap. A business intelligence strategy can include different elements depending on your industry, company size, competition and business model. However, the recommended ingredients are:
This is the documentation of the selected data source channels. These should include all types of channels, be it stakeholders, industry analytics in general or information from your employees and departments. Examples of such channels could be Google Analytics, CRM, ERP, etc.
Top 10 Guidelines For A Successful Business Intelligence Strategy In 2022
Documenting your industry standard KPIs as well as your specific ones can reveal the most complete picture of your business growth and losses. Finally, BI tools are created to monitor these KPIs by supporting them with additional data.
At this stage, define what kind of report you need to easily extract valuable information. In the case of a custom BI system, you can consider visual or textual representations. If you have already selected a vendor, you may be limited in terms of reporting standards, as vendors define their own. This section can also include the types of data you want to work with.
The end user is the person who will see the data through the reporting tool interface. Depending on your end users, you may also consider reporting
What Is A Business Intelligence Analyst? In 2022
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