"Data Lake," more than a new buzzword?! In the future, data analysis will make more comprehensive use of the various data sources of a company. The own data sources should be considered together with publicly accessible data as a big whole as a so-called "Data Lake".
The “Gartner Data & Analytics Summit” took place in Frankfurt on 23 and 24 October 2018. My fellow director Martin and I attended this event to learn about current trends in data analytics. Buzzwords such as artificial intelligence, machine learning, cloud analytics and NPL (Natural Language Processing) are on everyone’s lips and it’s obviously important for us to gauge the current status quo and look at what the future could hold.
The second episode of our interview-podcast is now available online. After the successful first episode of the interview between professor Winkelmann and Stefan Wenig and me, the sequel of the talk is available on several online portals.
In this blog post I will show you how you can objectify and automate risk assessment within your company by linking it with data analyses.
Risk management has always been a key element of a company’s management process. Risks are identified and assessed, measures are taken to mitigate risks and new assessments are performed at regular intervals. This process is present in many companies. Risk assessment is often based on a professional judgement of one or more managers. But why should it always be individuals who have to re-assess risks when data can supply far more objective criteria? With its autumn 2017 release, ACL GRC prepared the way for data-driven risk management. I will now proceed to explain the Assessment Drivers (“key assessment factors”) and the associated benefits in more detail.
When analyzing data in checks or audits, you often find that not everything which looks like a problem really is one. You may frequently check whether compulsory entries in the data are missing, and then possibly deduce problems in data consistency – sometimes your conclusions prove to be false.
In this blog post we want to look at the question of why open items in accounts payable can be well worth a closer look. We will illustrate this taking data from an SAP® IDES system; we will look at the data with ACL™ analytics software.
This year Audit Challenge 2016 (http://audit-challenge.com/) took place from June 20 through 24 in Frankfurt. As part of the event we had the opportunity of delivering a practically oriented paper titled "10 years of successful data analytics" together with Anke Giegandt of BSH Hausgeraete (formerly BSH Bosch Siemens Hausgeraete).
For 11 years now we have been offering digital data analytics by ACL™, and in this blog post I would like to tell you a few reasons why. Why is our choice ACL™? Of course it helps if you like to use the software you are working with (in our concrete case have even been selling since this year started). But must it really be ACL™. What about Microsoft Excel™ or Access™ or other data analytics tools like IDEA?
This time I would like to look at an article by Kerstin Daemon headed "Big data in business — when the firm knows when you want to quit before you do", which appeared in the April 15, 2015 issue of "Wirtschaftswoche" [WiWo1] and "The great data chaos of German business" by Meike Lorenzen published April 12th, 2013 [WiWo2].
For a number of years now process mining has been a subject in the world of data analysis that analysts are increasingly focused on. We too have already devoted a blog article to this methodology and gathered initial experience in projects of a different scale and with different tools. Through this series of articles I would like to offer insight into the experience we have managed to gain.
For a number of years now process mining has been a subject in the world of data analysis that the analysts are increasingly focused on. We too have already devoted a blog article to this methodology and gathered initial experience in projects of a different scale and with different tools. Through this series of articles I would like to offer insight into the experience we have managed to gain. After explaining some basic terms I will take a look behind the scenes to make two points clear: