ality check and will eventually use this year to develop their next-decade strategy, as far as data is concerned.
First of all, AI, ML and the Internet of Things (IoT), and of course full process digitization will be a focus for companies. They see them as required capabilities, and therefore are willing to invest in more digital innovation. Read more
We have already talked about the importance of good risk analysis and management for every kind of organization. On the other hand, poor risk management has the ability to impact your business severely on each level. Let’s have a look at the potential consequences that this could lead to. Below you can find 5 of the most significant impacts of poor risk management as well as what you could do about them, or avoiding them. Read more
With the hit of the digital revolution, the outlook and the parameters of data science underwent a serious change. The world nowadays is creating more and more data which causes the need and the emergence of new technologies and roles in the field of data science. Read more
Data governance is a requirement in today’s highly competitive enterprise environment. It would actually be correct to say that data governance is not a matter of option. It is a must for every organization dealing with large amounts of data. The management, as well asthe proper usage of the information across an organization is what leads to success. Data governance ensures that the data is trusted, secure, compliant and easy to find within your organization. Read more
When one starts the planning process for a project, one of the main things (or the main one) of your planning makeup is risk itself. In other words – what could possibly and eventually go wrong? To many of you it may sound as а negative mindset but it is in fact a preventative one. Issues are an integral part of every process, but if you have a strategy in mind to tackle them, risk will be minimized and managed. Read more
In our previous articles we went through the skills, required for a business analyst and also how his responsibilities differ from those of an agile business analyst. Having these in mind, there has been a notable increase in confusion when it comes to business analysis and technical business analysis too. These terms have widely been used as synonymous, but there are a number of prominent differences between them. Read more
We already went through the main skills that a business analyst should be equipped with. They can roughly be categorized in three categories: fundamental, technical and BA (Business Analyst) skills.
There is this term and profession emerging – and agile business analyst. What exactly does it mean and in what way is it different from a business analyst’s profession? Read more
Data management is quite similar to managing one’s health. If you do not pay attention to your health, eventually you will get sick and if you continue neglecting it, then you will suffer from poor health. And this is quite hard to manage unless you are ready to make drastic changes in your lifestyle. Same applies to data – if you do not take care of your organization’s data, in the course of time minor problems will become so serious that a major surgery will be needed. That is to say: re-engineering of your organization’s entire data infrastructure. Read more
Over the last 20 years data has evolved a lot. And every organization is rethinking its data architecture. According to Gartner: “data architecture and technologies are rapidly shifting to become highly distributed”. A reason for this is the amount of data organizations nowadays have to manage. Read more
The increase in the adoption of business process management (BPM) and service-oriented architecture (SOA) has created a high demand for qualified professionals with a plethora of skills. The Business Process Analyst (BPA) role is quite interesting to many people and is definitely an excellent career to get into. Read more