Advance to Self-service Visualization

Take small steps and gain new valuable insights impact by moving from spreadsheet reporting to active Business Intelligence

About Alexander:

Experienced project manager within the areas of analytics, business controlling, business intelligence and data management. Motivated by complex problems involving data, strategy and people. Result oriented with a hands-on approach to identify and implement efficient, realistic and sustainable solutions.

How would you describe self-service visualization and what are some common tools businesses are using?

In a data driven organization it is impossible for a centralized BI department to create reports that addresses all questions from the business. Self-service analytics is about going beyond the classic self-service reports and enable business professionals to build their visualizations. Common tools are Power BI, Tableau, Looker and Qlik Sense.

What are the main issues faced for organizations unable to implement self-service visualization? – The drawbacks of spreadsheet reporting

Recurring manual spreadsheet reporting is time consuming. Analysts and managers often spend more time compiling the numbers than analyzing the result. Consequently, meetings become inefficient and follow-up questions call for yet more meetings. The underlying data for the analysis is hard to share and the data dumps in large excel files on SharePoint are a classic approach that easily kills any interest from colleagues to analyze further.

There’s a lot of development in implementing these self-service solutions, how quickly can a business benefit from self-service visualization? Benefits of self-service visualization

The very first benefit of self-service visualization is the time saved from compiling the data. Adding the reduced risk of errors in the process and real-time reports on all screens and devices and the bundle becomes even more compelling. However, the list of benefits doesn’t stop there. Analysts and managers will gain new insights from the powerful visualizations provided out-of-the-box by the BI software market leaders. Leveraging the automated AI/ML tools it becomes easy to quickly identify the key factors impacting the bottom line or provide a second opinion on the latest bottom-up forecast.

How to get started with the process of going from spreadsheet reporting to BI visualizations?

Start by constructing a wanted position together with business users. In parallel, initiate an assessment of the data architecture and quality. The wanted position is then broken down into a roadmap where the reports with high business value and few technical obstacles along the way are prioritized first. Involve the future business users in the project and work with a flexible model, allowing changes along the way as you discover the possibilities in the data. Stay focused on definitions and data quality and provide at least two new insights to secure the success and business value of the first use case. Learn from the first experience and plan for the next on the roadmap.

Our Services

We offer a broad range of services designed to help you wherever you are on your data journey, from building BI and analytics teams to modernizing architecture by replacing legacy environments with more versatile cloud-based platforms, developing new advanced analytics solutions or improving the performance of old algorithms that haven’t kept pace with your developing business.

Data and analytics transformation

A transformation addresses all the elements that allow an organization to run on data. It can be an overall transformation or isolated to a specific business area.

Advance to self-service visualization

Close the gap between reactive and proactive analysis. Take small steps and gain new valuable insights impact by moving from spreadsheet reporting to active Business Intelligence

Architectural modernization

We deliver capabilities by managing and storing data in flexible cost effective environments and move away from silos. We modernize businesses technology for data and analytics, often by moving legacy environments to cloud based platforms or hybrids.

Value driven advanced analytics

Utilization of AI and machine learning to develop self-contained automated solutions, in conjunction with your industry subject matter experts