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From Ingest to Insights: Building robust Data Lakehouses with Microsoft Fabric

Increase efficiency with Data Lakehouse and Microsoft Fabric, powered by our framework! Create optimal data flow, increased scalability and focus on the core business logic.

Computer Vision in the financial sector

Artificial Intelligence (AI) is becoming smarter and smarter every day. The sophisticated algorithms have gone from using huge computers to recognize pictures of cats, to now being able to use your face as a password for your phone.

Churn prediction in financial companies: How to get started

 

 

Satisfied customers are the foundation of most businesses. They generate a steady stream of income and are more open to upselling. At the same time, studies show that it costs five times as much to acquire a new customer as it does to retain an existing one. Therefore, it is important to focus on ho...

Five tips for getting Machine Learning into production.

Do you also have a feeling that your data contains more potential than your company is currently harvesting? Being able to extract deep insights from data or automate manual tasks with a data application often relies on Machine Learning as part of the foundation.

Responsible AI

This blog post takes you through three important focus areas regarding ethics and responsibility in AI solutions.

Technology and technical skills fail in the absence of purpose.

AI has enormous potential, and we see both willingness and visions of being more "data-driven" and leveraging data optimally. However, the good intentions to stay ahead with intelligent AI solutions are often met with the same challenge: How do you actually create value with AI? Read the blog post a...

What is Explainable AI?

In this blog post, we will take a closer look at what explainability means within AI, as well as the types of information that can be extracted from AI/ML models.

How to get AI out of the sandbox

Today, the door to AI is open for all businesses, but few are able to fully exploit the technology. In this blog post, you can read about the three primary reasons why AI often remains a toy in the sandbox - and our recipe for how you can get the full potential of AI across your organization.

Master Data Management: Dos and Dont’s

We have now, in a series of blog posts, covered the key topics within master data management. Perhaps you are already feeling well-equipped to dive into MDM in your own company – or maybe you just need that final piece to get started or move forward.

Master Data Management: Governance – Organization, Roles, and Responsibilities

 

In the last blog post, we talked about master data governance with a focus on data and the policies and guidelines that your organization must follow to ensure coordinated and systematic use of master data. In this blog post, we will talk about the other part of MDM governance – your organization, r...

Master Data Management: Governance – Data & Compliance

In a previous blog post in our MDM series, we have discussed how master data is collected, modeled, cleaned, quality assured and shared for operational and analytical purposes. In this blog post, we will talk about how to ensure that the data you share in your organization lives up to your internal ...

Demo: Learn about Tabular Editor

 

Are you a Power BI user or do you work with data modelling in Analysis services? Then take a look as Daniel Otykier gives a thorough introduction to his tool, Tabular Editor. It’s four hours of learning that can save you countless hours of work.

3 new Power BI features we are looking forward to

 

At the beginning of May, Microsoft held their Business Applications Summit online conference. Here, they revealed lots of exciting new features and concepts across their entire Power Platform and D365 product palette. As Business Analytics consultants, we are naturally particularly interested in new...

Three areas where Machine Learning can generate more value for your CRM initiatives

 

Customer Relationship Management (CRM) is a big expense which can be very time consuming. Even though you may have a CRM system that meets all your needs, Machine Learning (ML) can help you take the extra step needed for meeting your customers’ needs even better than your competitors.

4 new developments in Power BI which we are looking forward to

The annual Microsoft Ignite conference commenced in week 39, and this time it was online and with free participation, which is of course what we did. In this blog, we’ve gathered the four new developments for Power BI which we are most enthusiastic about.

How can a dedicated consolidation solution improve process efficiency and generate value in your company?

Consolidation in companies with several legal entities is part of the fixed monthly and yearly financial processes. Consolidation in its simple form is the combination of the group accounts in order to be able to report one result across several entities and groups.

Master Data Management - what and why?

 

Master Data Management has been on the agenda for many companies for some years now, but only in recent years has there been particular focus on introducing management of the company’s Master Data as a discipline.

Master Data Management: Golden Record

This is another blog post in a series where we go into depth about typical problems within Master Data Management and how to resolve them. In this blog, we will define a Golden Record and explore how you can create one.

Master Data Management: Quality measurement and overview

This is the third out of six blog posts in our series about Master Data Management. This time, you can learn more about quality measurement and overview.

What is Azure Synapse Analytics and how can you use it?

Following the announcement back in December 2020, where Microsoft announced that Azure Synapse Analytics has now reached General Availability, this article will discuss the functionalities in the new analytics service in Azure.

BI Governance – hard, but you know it’s necessary

Do you recognise this? The network drive, SharePoint folder, your own desk. Regardless of the media, something happens when you use it. There is a good term for this – a mess. And much like the mess in the drawers of a teenager’s room and in the glove compartment of the car, there is a solution: Get...

Get control of the annual closing with Digital Finance - and some thoughts on 2020

Annual closing is primarily characterized by getting things organized, recording everything, and getting control of the many reconciliations and documentation for the audit. Data must be prepared and shared, and here you can advantageously use your data platform to optimize the process.

How do you drive successful data projects that create value?

Leadership sponsorship, early and ongoing involvement of business users, and a good deployment plan are the key to realizing value from your investment in data projects.

The role of the controller in the future – become an economic business partner with data skills

The finance department is undergoing a continuous digital transformation, where several tasks are being automated. This often happens with the use of new cloud technologies within ERP and BI. This development means that the traditional role of the controller as an Excel expert, solving a range of pa...

How to get good financial data: 4 typical challenges and how to solve them

Have you invested in a Business Intelligence (BI) financial solution for your reporting, but found that the solution is not working optimally in your everyday work? Or are you on your way to starting your BI journey, but don't quite understand the technology behind it and the language that IT speaks...

Make Business Intelligence and data analysis an integrated part of the monthly closing process

The increasing use of data and the heightened demand for compliance puts pressure on the finance department during the monthly closing process. With BI and data analysis, you can minimize the time spent on data collection and processing, freeing up more time to create an overview, analyze, and repor...

Consolidation of financial statements: challenges and how to solve them.

Consolidation of financial statements is complex and can be time-consuming with many manual processes - but with the right tools, manual processes can be streamlined or even automated.

Cloud Data Warehouse: These activities should be included before, during, and after your project 

We have gathered the most important factors that you need to be aware of to obtain an agile and forward-thinking Cloud Data Warehouse for your business.

Computer Vision: An image tells more than a thousand data points

 

A picture tells more than a thousand words. At least for humans. But how much does it tell a computer? Until relatively recently not so much. Instead of seeing cute cat pictures and cute puppies, computer programs saw ones and zeros. But that time is over.

How do we support the BI users' desire for self-service while ensuring optimal use of resources?

Many analysts and controllers desire great freedom to experiment with data, but how do we generally avoid the usage of data becoming too manual, thus not using company resources in a good way?

BI teamwork: How do you get a good collaboration between business and BI/IT?

 

A known problem regarding BI projects is the lack of cooperation between the business and the BI team/IT. Read our recipe for good BI teamwork here.

From data to BI solution – does the BI team deliver users dream?

The dialogue between the data users and the BI department can be difficult at times, and it is not always that the users feel that they have the BI solution they need. Here we give you the recipe for what needs to be covered, so you ensure that users get exactly the BI solution they are dreaming of.

Self-Service BI – what does it mean for different users?

 

Many BI departments are in a dilemma where the pressure for Self-Service BI is big and the resources to support it are limited.

We want to be data-driven, so why don’t users use our BI solution?

 

Read our suggestions of why many good BI solutions are not used – and avoid that the investment in your own BI solution is not wasted in advance.

Customer Retention: What is it and why is it important?

 

A new customer costs five times as much as retaining a current one. For that reason, you should focus just as much – if not more – on retaining your current customers rather than getting new ones.

How to get from Customer Churn to Customer Retention

 

Your customer data can tell you a lot about which of your customers might be about to leave you but how much does it actually take? What specific information do you need in order to make a prediction of Customer Churn?