Structure Business Intelligence Software

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Structure Business Intelligence Software – Business Intelligence is the means of transforming raw data into useful insights. It allows you to collect data from different sources, organize it, and then leverage the analytics. You need this? Probably yes, as it is the most balanced view of the business you can have. But as you can imagine, starting such a complex endeavor requires some preparation and we look forward to helping you with that. And if you have already introduced some BI procedures in your company, this article will also help you get organized. Now, let’s talk about your Business Intelligence strategy. Why You Need a BI Strategy A BI strategy will allow you to solve all your problems and data needs, develop a cohesive system, and maintain it. What happens when you start implementing BI without a strategy? Basically, you focus too much on getting these charts, but no one in the company understands why and how to use them. Here’s a helpful illustration of the before and after life of a BI strategy.

Previously, we published a guide for implementing BI practice in your organization. Now, we detail one of the steps in your implementation plan – documenting a BI strategy.

Structure Business Intelligence Software

Vision. Why are you building a BI practice at your company and what do you want to achieve?

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Tools and architecture. What dashboards and solutions do we want to build? For which areas? And how will they impact these areas?

So, when analyzing your company’s corporate strategy, you imagine which BI initiatives you want to initiate. So this vision helps you choose the right people who will use and maintain the chosen processes. To support people and processes, you use software tools. And finally, you establish the architectural design for your development. Now, let’s go into detail about these steps. And we will start with those companies that already have some form of BI. Step 0. Assess your current BI ecosystem To know where you’re headed, you must set a baseline. Let’s say you know that several departments have been using analytics, but the data is mostly siled – marketing people don’t have access to sales information, and customer support is tracking user feedback for their own internal purposes, or perhaps There are no reviews at all – basically it seems to work, but the effectiveness is unclear.

Therefore, the first thing to do is talk to all those involved in current BI processes: users and IT team, department managers and stakeholders. As a result, you should have answers to the following questions:

Then compile a SWOT analysis to organize what you found. SWOT analysis, one of the main strategy-building tools, will help you reveal your key strengths and problems for the next step. Step 1. Create the vision A vision is a combination of purpose and direction. There is no strategy without vision. It manifests itself in the form of many crucial decisions, such as what data we will obtain or who will have access to the insights.

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A vision also has a very mundane purpose: to explain to the people in your organization – who already have their favorite tools and processes – why they need new ones and how the transformation will happen.

Our corporate vision for BI is to create and support an infrastructure with secure, authorized access to data held anywhere in the enterprise. Our corporate standard for a BI tool is ________. We equip and evaluate our BI competency center based on end-user satisfaction surveys and successful deployments. An important segment of our end user community requires access to near real-time data. So we provide that infrastructure to accommodate them. We currently support ___ users who represent ___% of our user population. Our goal is to increase usage by ___% by (date). We weigh the potential costs of increased BI usage against the business value and ROI we receive. So we have a clear vision of our success that is measured, accountable and defensible.

Biere also notes that a vision articulated in this way will help fend off executives whose only goal is to provide employees with cheap tools and get back to “real work.”

Finally, the vision is usually accompanied by the BI Maturity model – the scale that indicates how mature your strategy is. You can find some interpretations of maturity models on the web, a very popular model coming from Gartner. According to them, there are five maturity levels for BI: Unconscious, Opportunistic, Standards, Enterprise, Transformative. Using these templates helps you identify your areas of advancement and what your next goals might be.

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Step 2. Establish BI governance processes BI governance deals with defining and implementing the BI infrastructure. (Not to be confused with data governance, which ensures consistent use of data across an organization.) This includes three components:

BI Governance Team Define BI governance members, their roles and responsibilities, roles, objectives, and relationships with different structures in your company. Involve people at all levels, from executives to end users, to bring all your perspectives to the table. Therefore, it is not exactly a group of BI experts, but rather a council made up of representatives from different areas of the company.

Larger companies, however, would benefit from an all-expert group in a Business Intelligence Competence Center (BICC). BICCs help identify data needs, establish data governance frameworks, oversee data quality, and overall data integration processes. They are programmers, scientists and data analysts, experts in relational databases and reporting tools. We recommend establishing such a team if you have a pool of experts to spare or the resources to hire them. BI Tools and Lifecycle Management The BI lifecycle is a framework that supports BI efforts, or specifically the architecture and tools used to do so. Typically, the architecture looks like a pipeline starting at the data sources (your ERP, external sources, etc.), then following a data integration process or ETL, where the data is transformed and loaded into the repository (data warehouse and data marts) before the data is finally displayed in dashboards and interactive tools. There are some architectural styles with different configurations of system elements.

Choosing BI tools. Depending on your confidence level, you can get an end-to-end platform or create your own mix for each phase of the BI process. You can also find a perfect match in terms of price or depending on whether you want to deploy on-premises or in the cloud. Use our guide to the best BI tools to help you with this task.

Business Intelligence Strategy: Creating Your Bi Roadmap

Development of the data integration process. Define data sources and make sure your BI tool can evaluate them. Ensure data is of high quality and establish processes for data preparation. Consider the architecture of a data warehouse.

Ensure data presentation. Establish what types of reports and dashboards your system will display based on end user needs and KPIs. Use our guide for some data visualization ideas, where we also list some useful tools and libraries.

Carrying out user acceptance tests. User acceptance testing is an often overlooked but critical process where you ask end users to perform some tasks and collect output information about the usability and performance of the system. Then you prepare the test cases, choose the test time, and choose the necessary tools.

Carrying out training. End users must be trained to understand data fundamentals and use a visualization platform. Before that, governance team members who are not proficient in BI must be trained to understand the data transformation phases. Basically, recognize where there is a knowledge gap and make sure you fill it as quickly as possible. User support In addition to training, prepare to assist users and solve their problems. Set up the feedback process and decide how you can react to it as quickly and cost-effectively as possible. Having a user support structure means you cover them from three points of view:

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Data Education Support – Provides the knowledge base to enable users to find the answers they have about the data they receive: metadata, data purpose, metrics, data source, and so on.

Tool support – If possible, choose the tool with end users, then establish agreed time frames for responding to the issue and communicate which channels or contacts they can use for support.

Business Support – Make sure end users not only understand the data, but know how to extract value from it. Assign mentors in each department to help users learn how to add value through BI tools, what metrics and dimensions to look for, and how to identify data trends.

Having decided how you will approach all of these BI lifecycle tasks, prepare your roadmap. Step 3. Create a BI Roadmap Here, a roadmap is a visual document that demonstrates the results at different stages of implementation within the timeline. At this stage, you already have all the necessary data to organize and schedule on the map, simply setting deadlines and deliveries for each task.

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The roadmap may only cover high-level tasks like “Find a BI vendor” or be reduced to “Create a top ten match list,” but for strategic mappings, the high-level overview will suffice. Below is an example of such a script covering three quarters. Has deliveries

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