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How to Successfully Adopt a BI Tool

Technology

Aug 3, 2020 - 5 minutes read

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Objectivity Innovative leader in technologies

Our specialty is designing, delivering, and supporting IT solutions to help our clients succeed. We have an ethical framework that underpins everything we do. Our underlying philosophy is that every client engagement should result in a Win-Win and this is supported by our four values: People, Integrity, Excellence, and Agility. Our clients are at the heart of our business and we are proud to form long-lasting working relationships, the longest of which is 29 years. Our goal is to continue to grow our business whilst remaining true to the ethical framework and values on which we are founded.

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The IT departments of many organisations have lately been flooded with requests for shiny new visualisation tools. The promise of dynamic, powerful dashboards, an accelerated time to market resulting from the use of a self-service platform, and independence from IT’s ‘longish’ delivery cycle all sound tempting. However, self-service Business Intelligence (BI) tools are not an antidote to all your data problems and there are still elements IT must take into consideration before buying licences. So, how best to prepare your organisation before rolling out new BI software? 

Is a Brand New Business Intelligence Tool Enough?

Fortune 500 companies already know that data is their asset, moreover, they also recognise that data is basically the newest form of currency. However, many organisations still struggle with delivering valuable insights from data at the right time and to the right people, hindering their efforts to take precise and timely action.  

Businesses are often overwhelmed with the manual workaround with regards to data preparation or are limited by the IT department’s ability to deliver new requirements. Often, business departments’ main tool of development is Excel and the automation is done in Visual Basic. Hence, it’s not a surprise that buying a new powerful BI tool that allows end users to prepare data, build colourful, interactive dashboards and scorecards, and share them with others without the need for mailing Excel files, seems to be the best way out of their status quo.  

Please don’t get us wrong – modern BI software is a powerful asset, but its release must be well-planned and based on a deep understanding of what happens with the data, how its processed, maintained and served. After all, data visualisation is only the final step of the data preparation process.

Top 5 Things to Remember Before Introducing a New BI Tool

According to Nucleus Research, Business Analytics delivers on average $13.01 for every dollar spent, but sometimes just forgetting a few simple things can ruin your project.

Before you spend a lot of money and effort on your BI investment, consider these important aspects to help render your introduction of a data visualisation tool effective and successful. 

1. It just looks so easy 

When buying a Business Intelligence tool, you may think that since it’s a self-service tool any Excel user will easily be able to use it without any special preparation and experience. Unfortunately, it’s not that simple.  

In fact, a lack of technical training is one of the most common reasons for the failure of BI projects. The entry threshold for using such a tool is not high. However, the user will need to quickly understand its more complex functionalities, such as: data modelling concepts, the tool’s programming language, visualisation techniques, and best practices. A lack of technical knowledge can result in inaccurate analyses and charts, wrong calculations, and can cause your BI applications to run more slowly, break frequently, and deliver uncertain results. 

2. Unprepared data means faulty visualisations  

Data preparation is one of those steps in a BI project that just cannot be omitted. It accounts for about 80% of data scientists’ entire work effort (Forbes). Depending on what kind of data you have in your organisation, it may require different skills and techniques – from SQL queries to programming in Scala or Python. On the other hand, more and more BI tool providers are trying to make their tools capable of pre-processing, e.g. Power Query Editor or Tableau Prep. Nonetheless, one thing is certain – before you start visualising, you need to clean, transform, integrate, discretise, and reduce the amount of your data.  

3. A good data model saves time and money 

Should we invest in building a data model? Isn't it an old-fashioned concept that’s rather incompatible with modern BI? These are valid questions, but let's think about the benefits of introducing a data model for a moment. A deep understanding of business processes, the possibility to integrate existing systems, no need to write the same query multiple times, faster data processing and calculations, simpler code, easier maintenance, and knowledge transfer are just some of the advantages. And, all this could be a result of a model predefined in the source Data Warehouse; it could be a virtual, semantic model or a model built and shared in Power BI or Tableau.  

4. Build trust in your data 

Data Governance has a key role in Enterprise Data Management. Good quality data builds trust and confidence during the decision-making process. To ensure trust is built and maintained, such topics need to be covered as: are we in line with compliance regulations and GDPR, is our data safe and secure (e.g. equipment failure, cyber attack, sensitive data), is the data available anytime you need it, and do you have maintenance and a recovery plan. 

5. Cloud as a solution for infrastructure challenges

By 2022, public cloud services will be essential for 90% of data and analytics innovation (Gartner). Cloud managed services accelerate data projects delivery and reduce the need for administrative skills in your team. However, cloud deployment should be planned carefully, with a deep understanding of architecture dependencies and the purpose of the services used. Only well-planned and precise cloud adoption allows for the successful deployment of data solutions at a low cost. 

Summary 

Although the Business Intelligence world is currently focused on data democratisation and enabling citizen developers, IT’s role is still crucial. Finding the right balance between self-service analytics and IT ownership of critical elements, such as data governance, smart data preparation, data modelling, well-designed infrastructure, and appropriate training, is the key to success. 

If you’d like to find out more about how data can help you transform your organisation, download Objectivity’s latest complimentary eBook: “How to Build a Data-Driven Organisation”.

About the Authors 

Julia Orłowska 

BI Practice Leader with a strong technical background in Objectivity’s Data & AI department. Focused on building a multiskilled team able to consult, design, and deliver enterprise BI solutions for a variety of clients. She’s been leading, consulting, and developing BI projects for over 10 years, from simple reporting solutions to complex, fit-for-purpose data systems, which enable companies to become data-driven. 

Jadwiga Józefczyk 

Senior Business Intelligence Analyst in Objectivity’s Data & AI department. She’s passionate about information design and data storytelling, with a strong background in statistics and over 8 years of commercial experience in data analytics. She’s fluent in leading BI tools and works closely with multiple clients, keeping their business needs at the forefront.

Data Driven Organisation Blog Ebook 416X300
Objectivity Innovative leader in technologies

Our specialty is designing, delivering, and supporting IT solutions to help our clients succeed. We have an ethical framework that underpins everything we do. Our underlying philosophy is that every client engagement should result in a Win-Win and this is supported by our four values: People, Integrity, Excellence, and Agility. Our clients are at the heart of our business and we are proud to form long-lasting working relationships, the longest of which is 29 years. Our goal is to continue to grow our business whilst remaining true to the ethical framework and values on which we are founded.

See all Objectivity's posts

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