Providing ample business intelligence in clear, concise fashion is important for every business. But, if the business analytics tools are not simple enough for business users, all that sophisticated analytical data will not help your team to make confident decisions or to accurately and effectively plan.
‘R’ is not just a letter in the alphabet! R is a programming language, offered in a free software environment that supports analysts, IT and data scientists in doing tasks that require statistical computing. The R language is very popular and is used in many organizations around the world to support statistical analysis and data mining. When a business implements a business intelligence solution, IT staff, data analysts and data scientists are often put into a quandary. The enterprise is actively using and benefiting from R but the BI tool the business selected forces them to choose between tools to get the job done.
We all know the frustration of seeing something you really like, something you really need and then finding out that the price is not as low as you thought. Whether it is an item of clothing or those concert tickets with all the service fees added on, you know what I am talking about.
Today’s businesses and business users are more demanding than ever. No one has patience these days for tools, applications or products that offer no value or are frustrating or restrictive. So, when you hear the term ‘self-serve business intelligence’, you had better be sure you know whether the claim is valid before you choose a product.
Augmented analytics can help your business users to find and understand critical data and to do their jobs more effectively. Without the knowledge of a data scientist or an IT professional, business users can perform advanced analytics, using features that guide and make recommendations at every step so that data is prepared, viewed and analyzed in a way that ensures clarity and a comprehensive understanding of trends, patterns, and data sensitivity and success thresholds.
An enterprise that employs restrictive business intelligence tools is losing competitive advantage and crucial business opportunities every day. To get the most out of business intelligence software, an organization needs a self-serve business intelligence dashboard that will allow business users to access data integrated from multiple sources and analyze that data with ease, using business intelligence reporting that incorporates sophisticated features in a simple, interactive environment.
There is a new business role on the horizon and, at first glance, it may seem very much like a role that was introduced a few short years ago. This new enterprise role is known as an ‘Analytics Translator’ and, while there is some confusion regarding the distinction between this role and the newly minted Citizen Data Scientist or Citizen Analyst, there are some subtle but important differences. In a previous article (What is an Analytics Translator and Why is the Role Important to Your Organization?), we discussed the definition of an Analytics Translator. Here, we will discuss the role of Citizen Data Scientist and Analytics Translator and how they differ. To understand these roles, let’s look first at the somewhat more familiar role of Citizen Data Scientist (AKA Citizen Analyst).
Your business users are ready to do the job! They have a lot of data spread across the enterprise in various data repositories and forms and they want to pull it all together and analyze the data to get the answers to the questions you ask them every day. But, preparing that data is not easy.
Today, enterprises recognize the critical value of advanced analytics within the organization and they are implementing data democratization initiatives. As these initiatives evolve, new roles emerge in the organization. The newest of these analysis-related roles is the ‘analytics translator‘. As the enterprise considers the relevance of this new role within the business, it is important to understand the responsibilities of an Analytics Translator, and how this role might help the organization to achieve its goals.
Self-serve business intelligence tools are no longer new. Nearly every BI tool vendor has an offering in the market. But, not every business intelligence tool is equally useful.
