Business Intelligence: The guide for organizations

Self-Service BI allows end-users to access data and perform data analyses without direct support from the IT department. This approach is particularly useful for organizations that do not have a lot of resources, but still have a high demand for data, where IT analysts cannot keep up with query requests. Basically, the goal of self-service BI is to simplify data management in the organization. Follow the link for real-world examples of how cash flow, P&L, and marketing data can be managed more efficiently and profitably.

As we have seen, business intelligence tools are effective instruments that help organizations use their data effectively and make informed decisions. However, despite these benefits, BI tools also pose challenges to users because they require specialized knowledge in a variety of areas:

• Data collection: Aggregating data from different sources is a complex task, especially when the data is unstructured or comes from multiple systems.
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  Data integration: Integrating data from various sources into a data warehouse becomes a challenge when inconsistencies or duplicates exist.

Data preparation: Before data can be analyzed, it must be cleaned, transformed, and validated. Learn how crucial this process is in this article: Data Cleansing: The Comprehensive Overview for Ensuring Data Quality in Companies

Data visualization: Presenting data in an easily understandable form requires both technical know-how and a grasp of statistical and information technology concepts. The data must be screened, visualized, and validated.

This complexity results in static structures and processes within organizations, creating a strong dependency on BI experts who can effectively utilize these tools.

Problem 1: Adaptability: External data sources and systems like online shops, CRM systems, or other external data sources can be difficult to integrate, meaning there is a lack of interoperability.

Problem 2: Accessibility - lack of self-service: Not all employees have the necessary training or experience to effectively use BI tools. This can create a gap between data analysts and other departments, making the process static.

Problem 3: Time and resource constraints: Both data analysts and other specialized users, such as those in controlling, sales, or management, have limited time available. Therefore, an effective and practical solution is needed: Rely less on complex BI tools and more on customized BI applications that provide individual end-users with exactly what they need.

In a modern organization, each department has its unique data requirements. BI can help meet these needs and optimize workflow. The integration of BI into daily organizational operations is more than just a trend today; it's a necessity to remain competitive in a data-driven world. Naturally, different departments have individual needs that pose varying solutions and requirements for IT.

For a concrete implementation plan, see our BI Reporting Compass.

In the realm of sales, the focus is on customer acquisition and revenue growth. Business intelligence allows sales teams to deeply analyze customer data to identify potential sales opportunities and precisely adjust sales strategies. A concrete example is the ability to determine, based on data, which products are most saleable in specific geographic regions or to recognize seasonal sales trends. This comprehensive understanding of the data landscape enables targeted actions to optimize sales strategies.

Controlling is responsible for monitoring and steering the financial performance of an organization. Self-Service BI proves extremely valuable here, as it provides controllers the opportunity to analyze financial data in real-time to monitor budgets and create profit and loss statements (P&L). Moreover, this data can be used to identify cost overruns in specific departments or assess the profitability of investments. These insights enable controllers to make informed decisions to ensure the financial integrity of the organization.

Accounting deals with the recording and reporting of financial transactions. With Self-Service BI, accountants can process financial data more efficiently and generate reports more quickly, as they have better access to the required data themselves. For example, they can use the data to identify discrepancies in accounts or monitor cash flow. By automating these processes, they save time and improve the accuracy of their reports.

Business intelligence supports leaders in accessing data dashboards from various departments to get a comprehensive picture of the organization's key performance indicators (KPIs). This data is used to identify market trends, assess employee productivity, or measure customer satisfaction. With this informed knowledge, data-driven strategies can be developed to successfully advance the organization.

Access to data shouldn't be reserved for just a select few. Without Self-Service BI, the process usually works like this:

• The IT department and data analysts ensure that the data infrastructure is functional and secure.
• Data analysts are then responsible for analyzing the desired data and providing it in dashboards.

But what if every employee had the opportunity to access this data whenever they needed it? That's the promise of Self-Service BI. Data designated for various departments is made available through the data warehouse, allowing even non-specialists to retrieve, analyze, and gain insights from it. This makes the BI process more dynamic overall, but it also introduces new, different kinds of challenges that need to be addressed.

Dynamic data access offers many advantages, especially the ability for users to quickly search for desired metrics and KPIs and create reports. This can be particularly useful in areas where quick decisions need to be made. However, this approach also brings several challenges:

1. Administrative overhead: Although the IT department and data analysts are less involved in operational analyses, they have to invest more time in administration. This includes ensuring system performance, managing access rights, data backup, and data protection.
2. Unified vocabulary: With different departments conducting their own analyses, it can be challenging to establish a consistent vocabulary or standards for data and reports.
3. Data integration: Combining central data from the data warehouse with user-specific data can be complex and requires careful consideration to ensure data quality and integrity.
4. BI process maturity: Organizations need to assess the maturity level of their BI process to ensure they find the right balance between centralized control and user independence.

Reporting should not only be accurate and reliable, but also simple and easy to use. It's critical to reduce complexity and make the process understandable and accessible to all parties. The integration of self-service BI systems plays a key role in simplifying reporting. These systems enable users to perform analysis and generate reports on their own, without having to rely on IT. Learn more about how to ensure the quality of reporting in your organization in this article: Typical issues in creating and sharing reports following data analysis: An overview of report quality improvement.

Such a system ensures that all data used for reporting is consistent and of high quality. This reduces the risk of errors in reports and makes it easier for users to access the data they need. By combining central data from the data warehouse with user-specific data, reports can be created that are both comprehensive and customizable.

To fully leverage the benefits of Self-Service BI systems, it's important that users know how to effectively use these systems. This includes not only technical training but also training in data analysis and data protection. By strengthening the data competency of employees, they are empowered to independently create meaningful reports, thereby reducing dependency on BI experts.

For decades, Excel has been the preferred tool for data analysis and reporting in many organizations. It offers a familiar environment where employees from various departments can analyze and work on their data. The flexibility and user-friendliness of Excel have made it an indispensable tool for the daily work of many professionals.

The strength of Excel lies in its simplicity and accessibility. While it does require specific technical skills, these are now widely spread across most organizations. With Excel, data analyses and visualizations can be performed with just a few mouse clicks. This makes it an ideal BI tool, especially for organizations that already use Excel as a central tool.

While Excel is a powerful tool for data analysis, there are limitations that specialized BI solutions can overcome. This is where AnalyticsGate comes into play. We recognize that many organizations and individuals want to leverage the benefits of Excel but also require the advanced analysis features of specialized BI tools.

Our solution combines the best of both worlds. With AnalyticsGate, you can continue to work in your familiar Excel environment while also accessing powerful BI features by simply linking the Qlik Sense database with Excel.

The key differences between Self-Service BI and Enterprise BI have been outlined, with each approach having its own advantages and challenges. While Self-Service BI allows end-users to conduct data analyses independently of the IT department, Enterprise BI offers a unified solution across the organization. Despite the benefits of BI tools, there are also challenges, particularly concerning the complexity of the tools and their integration into various business areas.

Organizations that effectively deploy BI are better equipped to make informed decisions and compete in a highly competitive market environment. However, it's crucial for companies to choose the right BI solution that meets their specific needs and to invest the necessary resources to optimize their BI processes. With the right approach and tools, organizations can fully leverage the benefits of BI and achieve their business goals more efficiently.