Six misconceptions about algorithms
November 2018Misunderstanding algorithmsArtificial Intelligence is a hot topic. Algorithms can determine the notes of a new perfume. The high-art world has been scooped by a portrait painted by an algorithm and signed with the code: minG maxD Ex[log(D(x))]+Ez[log(1-D(G(z)))]. These are two random examples of relatively innocent, yet surprising, applications of AI. However, algorithms can also inspire fear. Crashing self-driving cars, smart speakers that take over the entire house, algorithms that thoughtlessly dismiss job applicants based on gender or sentence suspects without mercy. Can algorithms be used for the good of mankind?
The 12 biggest growing pains in becoming a mature BI organization
November 2018Learn from the growing pains others have overcomeAs project leader, you’re cradling an ambitious BI project, and you’re looking for theoretical and (especially) practical frameworks. You know that you can achieve better results using the right management information. Googling “Business Intelligence” returns 527 million results. “BI Tools” narrows it down a bit, but still returns 855,000 hits. Discussions are spreading out in all directions and it’s hard not to get dizzy. If you want to get serious about working with BI, it’s easy to end up in a roller coaster. You’ll want to get both feet on the ground again as soon as possible. But BI is dreaming, daring, and especially doing. But you don’t have to start from scratch; you can learn from the growing pains that others have already experienced. The road to hell is paved with good intentions. after all. Learn to recognize these symptoms and avoid them, or deal with them. This stories are based on the goals and ambitions of the hundreds who have taken our Business Intelligence training course.Doing more with lessI can’t make the business caseGetting lost in the “jungle” of BI tools Are we using the right management KPIs?I feel like a toy of demanding usersData Science Book
6 reasons not to build a Data Lake
October 2018A lake of dataIn this technology-driven world, we like to believe in progress. It can be easy to forget that “new” isn’t always better. A prime example of this is the “data lake” phenomenon: a figurative lake of data, which became a hype in Business Intelligence (BI) and Big Data circles. Many companies rushed to jump on the bandwagon and built their own data lake. But was this such a good idea, or would it have been better to think about what can be accomplished using a data lake first.What is a data lake?Monitor your data quality/”Hire a Business Intelligence Consultant Visit Passionned AcademyData Science Book
5 Steps to becoming an Intelligent Organization
October 2018Make your organization intelligentAs a leading consultant in Business Intelligence, we offer a small but high-quality range of Business Intelligence services. Our Business Intelligence guide focuses on what you want to achieve in the near future, what the business benefits are, and how to get there, in 5 steps.Business Intelligence RoadmapThe 101 steps to BI successData Science BookVisit Passionned Academy
The 7 biggest Big Data pitfalls
October 201860% of the Big Data projects fail to take offBig Data has many potential advantages. It can provide new insights into consumer behavior, show you in which areas the organization can work more efficiently, predict future changes, and much more. However, many companies forge ahead into Big Data without being adequately prepared, and charge straight into a pitfall. Research shows that about 60% of Big Data projects stumble out of the starting blocks. How can you make sure that your organization doesn’t become a statistic?
One algorithm can replace 100 reports
September 2018The old BI world and the new AI worldBusiness Intelligence has been used to help organizations work more information-driven for years, and it’s showing no signs of stopping. According to Daan van Beek, CEO of Passionned Group and author of the Data Science book “Data Science for Decision Makers & Data Professionals”, BI still serves as an umbrella term, and even covers the Artificial Intelligence and Big Data hype. We had a conversation about data-driven working and the careful balancing act between the ‘old’ BI world and the ‘new’ AI world.What is machine learning?The sense and nonsense of big dataTop 7 Big Data trends 2023Visit Passionned AcademyData Science Book
The Ethics of Big Data: temptation and fear
November 2017Big Data philosophyEthics is a discipline in philosophy primarily concerned with discerning what forms of human behaviour are acceptable and those that are not. More generally, ethics (or moral philosophy) is a sub-section of philosophy that deals with recording, defending and supporting the concept of good and bad conduct.What is Big Data?Big Data examplesHire a Data Analyst5 Principles for responsible AI
The 7 habits of highly intelligent organizations
November 2017Disruption effects one sector after the otherIt’s said that wisdom comes with age. Does this also apply to organizations? Do they become wiser and smarter as they get older? There are examples of old-fashioned companies. They constantly reinvent the wheel, such as IBM. But think of beverage producers like the Brand (since 1340), Bols and Grolsch. They have existed, and managed to survive, for a very long period of time. These types of organizations are an exception. Disruption runs rampant and affects one sector after the other. In the 1920s, the average company age was 65 years old. That number has come down to 15 (Yale University). Incidentally, this research also indicates that the top 10 of the oldest companies contains three beverage manufacturers.5 steps to become a more intelligent organizationBalance investments in people and technologyData Science BookOne algorithm can replace 100-reportsHire a BI Consultant
Zoetermeer shifts from financial to business control
September 2015Increasing public valueMunicipalities are working to make an impact on citizens and entrepreneurs. The key question here is “How can we increase our public value?” This means that organizational competencies such as results orientation, performance orientation, continuous improvement, and innovation are important in order to properly demonstrate its function in societal participation. In short, municipalities must explore new avenues. 5 reasons controllers should dive into AI Invest in people and technologyOne algorithm can replace 100-reportsData Science BookHire a BI Consultant
Why every controller should know everything about Big Data
July 2015Don’t miss the boatControllers like to keep things manageable and help organizations with keeping KPIs in order. This is understandable and good from a risk management perspective, but modern controllers must now know everything about Big Data. This is because established KPIs and manageability have to clear the way for Big Data and innovation. Organizations that lose sight of this transition risking completely missing the boat.Definition of Big Data Different types of KIP’sBalance investments in people and technologyData Science BookSmart KPI ToolkitBig Data Training
Rotterdam on the way with information-driven working
June 2015Rotterdam lifting offIn 2014, the Rotterdam’s community wanted to bring more cohesion to all BI activities. It started with information architecture and the description of a strategy. A pilot project focused on school dropouts, along with Passionned Group, must now show how it works in practice. The book ‘Data Science for Decision Makers & Data Professionals’ of author Daan van Beek served as inspiration here.What is data-driven working? Data-driven working: say goodbye to the status quoBalance investments in people and technologyData Science BookHire a BI ConsultantSmart KPI Toolkit
5 crucial requirements for KPIs
February 2015How do you define genuine KPIs?If you want actionable management information, you need genuine KPIs. To ensure that users understand the information as quickly as possible and that they can define actions, the Intelligent Organization will have to take into account a number of generic requirements (see below) that should be imposed on management information and key performance indicators. You can also check the SMART KPI Toolkit 2024, or contact one of our KPI specialists for more information, advice or KPI examples.
The 5 Biggest Benefits of Analytics
December 2014Information democracy is boomingIn recent years, Business Intelligence and Analytics has become more relevant and as a result gained a much larger audience. In the past managers formed the main audience but nowadays we see that many Business Intelligence applications are also being created for knowledge workers. There are two reasons for this change: firstly, the booming information democracy and secondly, the fact that knowledge workers, to an ever greater extent, are urged to make independent decisions and solve problems quickly. In this article, we examine the benefits of Business Intelligence for managers and knowledge workers from various angles.The 7 biggest blunders in Business Analytics The 101 steps to Business Intelligence success Hire a Business AnalystData Science BookBI & Analytics Guide
Increase the hits on your data warehouse with Google
November 2014Deliver information to the userData warehouses typically contain quite a lot of content. Let us assume, for convenience sake, that much of this content is relevant and reliable. This is often not (yet) the case, but fine, we want to address another issue here, namely that the user cannot find information even though it is available in the right quality. In this article we present a checklist and show you how you can profit by connecting Google to your data warehouse .
Managers develop the strategy
November 2014Ownership is the keyIn order to prepare an organization Cockpit, it is sufficient that the organization has a strategy at a certain point in time. However, writing a book on strategic performance management without ‘coming clean’ is not possible. Because, in strategy formulation, content, tools like Cognos and BusinessObjects, and process influence each other. That is also the reason that the leadership of an intelligent organization tries to make content and process reinforce each other.Define a good strategyHow to use a strategy map Making a sound BI roadmapSetting strategic goals in 5 stepsBI & Analytics Guide
The municipality of The Hague and Passionned collaborate on BI
November 2014It’s a really fun jobDaan van Beek and Wouter Huisman of Passionned Group have been supporting a project group of the Municipality of The Hague for some time. The goal is to achieve a municipality-wide Business Intelligence Roadmap. “In terms of business intelligence we are really still learning to walk,” says Ling Po-Shih, Group Advisor / Project Manager Business Intelligence (BI) at the Municipality. “In 2009 internal research showed that we were not at all ready for BI at the time. We did that research again in 2013. Now we are at the point where we want to draw up a BI Roadmap. We do, however, need some help with that.”Define a good strategyHow to use a strategy map Making a sound BI roadmapSetting strategic goals in 5 stepsBI & Analytics Guide
Powerful Business Intelligence at accountancy firm PwC
November 2014Reference casePassionned Group assisted accounting and consulting firm PricewaterhouseCoopers in the design and implementation of a powerful Business Intelligence system. Until recently this office managed on the basis of figures that lay hidden in collections of spreadsheets, stunning presentations and all kinds of downloads, in particular on financial indicators.The 101 steps to Business Intelligence successBI roles and competences ETL & Data Integration GuideHire a BI ConsultantBusiness Intelligence Book
The Carante Group takes next step in Business Intelligence
November 2014Reference case in the healthcareSince early 2014, the BI team of the Carante Group in the Netherlands has been working on the redesign of their 12-year-old BI environment. “On the one hand, it is about developing a new vision and a strategy, on the other hand we want to organize BI better and give it more body.” They are doing this with the help of Marc Wijnberg, senior BI consultant at Passionned Group.The 101 steps to Business Intelligence successBI roles and competences Self-service BIHire a BI ConsultantBI & Analytics Guide
The 5 biggest KPI blunders
October 2014KPIs and SMART objectives are powerful tools but tricky to masterMany companies and (government) institutions are paying more and more attention to the Key Performance Indicator (KPI) and SMART goals. This is logical because they are powerful tools for managers, improvement teams and controllers. Moreover, KPIs are at the heart of every organization, including yours. The trick is to find them, define them correctly and use them to adjust faster and improve your processes. But defining and steering by KPIs and SMART goals is a tricky business. A misstep is quickly made. Or before you know it you have way too many of them or a discussion arises about the definition. We have listed the 5 biggest KPI blunders and pitfalls for you. So you can avoid them in the future.
The 5 biggest pitfalls in predictive analytics
May 2014The five major pitfalls in predictive analyticsPredictive analytics is a powerful instrument for many organizations. It helps them to create competitive advantage and make their business processes more effective. Insurance companies and credit card issuers for example use it to detect fraud, cops use it to catch criminals, sometimes even before they commit a crime, and car dealers apply analytics to predict the chance that someone responds to a campaign. From our experience we strongly believe that there is a lot of added value in predictive analytics. But, prediction is very difficult – especially if it’s about the future (Niels Bohr) – and making automated predictions is even more difficult. There are many pitfalls on the road to success. We think this are the five most important pitfalls:What is Big Data Analytics?Six criteria for measuring data quality BI & Analytics GuideHire a Data ScientistData Science Book
Reduce waste by 10% with Data Analytics
September 2013New challenges to reduce wasteEven though there are many standardized tools, specific solutions will always have a place. New challenges demand tailor-made solutions. A cotton manufacturer wanted to work more efficiently and reduce waste. Critical questions spurred that desire on. The production team wondered: why do we do things the way we do them? Why are we throwing away so much good material? Can we do better?What is Big Data Analytics?BI & Analytics Guide Without data analysis, BI is pointlessHire a BI Data ScientistData Science Book
Business Intelligence roles and competencies
September 2013Key competencies broken down by functionAutomation is always about people. This is certainly true with regard to ‘automating’ decisions and transforming data into ‘actionable intelligence’. The point is that people will use this information and start acting differently. In order to create a proper (well-designed) Intelligent organization, we will need people in certain roles, with specific (behavioral) competencies, experience and knowledge, first on a project basis and later in the daily operations. In this article, we describe the ideal Business Intelligence project organization. Note that, in practice, we do not always require all roles or we cannot always facilitate all roles, due for example to budgetary constraints.A practical BI definitionBI & Analytics Guide Without data analysis, BI is pointlessBusiness Intelligence TrainingHire a BI ConsultantData Science Book
Top 10 BI risks and obstacles to success
September 2013High risk and highly politicalBusiness Intelligence projects are characterized by an extremely high risk factor and many obstacles. These obstacles are mostly related to the fact that Business Intelligence projects typically go beyond the boundaries of departments, processes and even business units; contain a mix of strategy, business operations and technology and are often highly political.A practical BI definitionWithout data analysis, BI is pointlessBI & Analytics Guide The 101 steps to Business Intelligence successData Science Book
Testing Business Intelligence systems
September 2013How can you test efficiently and effectively?If we do not predetermine what we test and how we test the Business Intelligence system, then this testing process can be very time consuming. BI allows flexible reporting. Precisely because Business Intelligence allows flexible reporting, we are initially tempted to test all possible combinations of indicators and dimensions. What we forget is that, even in small Business Intelligence systems with for example ten indicators that are linked to eight dimensions, the number of possible combinations can reach ten million!
The pros and cons of a Data Vault
July 2013The Data Vault: facts, fables and truthAt the heart of the Data Vault methodology is an ingenious modeling technique for data warehouses. It was put together by Dan Linstedt at the U.S. Department of Defense in an already distant past. A Data Vault stores all incoming transactions in a hyper-normalized structure. Regardless of whether this data has integrity and accuracy: “100% of the data 100% of the time”. The Data Vault distinguishes between facts and the truth. But who is waiting for the facts? In this article, read the main advantages and disadvantages, find the four differences between third normal form and Data Vault and finally arm yourself with the 10 irrefutable facts about Data Vaults.10 Data Vault factsData Vault advantagesData Vault disadvantagesData mesh makes data warehouse obsoleteBI & Analytics GuideData Warehouse Training
Nine reasons to build a data warehouse
June 2013Do you still need a data warehouse?More and more organizations are wondering what the use of a data warehouse is, and whether or not it’s worth the investment. They also want to know what alternatives are available. A growing number of IT vendors and some “experts” claim that the end of the data warehouse is nigh. When we say vendors, we’re referring to suppliers of data warehouse appliances, data virtualization tools, and data discovery tools. We have a different opinion, though. The data warehouse still is the beating heart of the Intelligent organization and it serves different vital goals.
Selecting BI tools
December 2012Choose the right tool for the jobOften organizations find it difficult and labor-intensive to choose the right BI software for the job. The in-depth and independent BI & Analytics Guide is designed to help you make a selection quickly and very efficiently. The BI & Analytics Guide may confirm your companies standards or preferences, or it is also possible that it will reveal that your companies standard should be updated.
Selecting an ETL tool
January 2012Explore the 7 steps to find the right tool for youChoosing the right ETL software for your organization can seem a daunting prospect. The task is difficult, labor-intensive, and it’s hard to find a good starting point. To support you, we’ve defined a step-by-step ETL tool selection strategy, based on our more than ten years of involvement in tool selection processes.✓ Expert opinions on 20 ETL tools
