CIOs explain that end users and IT employees have different vocabularies; to solidify a partnership, it’s necessary to explain the project in terms that are understandable to the clients
Enterprises acknowledge that data has turned into a critical asset, but only a small minority feels that they are actually in a position to leverage all the benefits that Data provides. CIOs say that very few of their decisions have been made better with data utilization, and few felt they were overwhelmed with data.
C-suite leaders say that the rate of data in-flow is so high that enterprises cannot keep up. It may also arise from the lack of clear communication within enterprises and with the end-users and clients.
CIOs say that one critical issue related to IT communications between IT and clients is that engineering departments tend to dominate the entire IT domain. This is mainly due to the difference in the vocabulary between the two groups. It is primarily due to the excessive use of technical jargon that confuses the client, resulting in complicating the path to productive Big Data use.
Enterprise leaders say that IT is the main decision-maker when selecting the tech for processing Big Data; however, end-users must be made aware of the basic steps of the process.
Read More: Google Tops the List of the Biggest Data Breaches and GDPR Fines
Developing a data model
CIOs believe that it’s vital for IT and end-users to be on the same page about the business process and what type of data is needed from systems to make it work. This process is generally referred to as the requirements and business process definition. In the Big Data world, the same is called a data model.
Every data model is divided into two parts. The first segment of the process involves users describing the business process on a device; they list the various types of data needed to complete the process.
In the second part, IT works to create the base data model. It displays how different computing resources, databases, etc., will collect the data. However, users aren’t needed to be involved in this complex and technical part of the data model design. They are needed only to confirm that the information requirements and business processes are completed.
Defining the algorithm
C-suite leaders believe that a basic explanation of the algorithm is vital in convincing the end-users. It is the search criterion used by the users to find the data. If users feel that the algorithm is not matching their requirements, the IT team can restructure the query and develop an improved version without wasting a significant amount of time and resources.
Read More: Can Encryption Boost Data Security
Harvesting data
Data collected from the data sources are then processed by the data models to remove incomplete, inaccurate, and duplicate data so that only high-quality data is sent to users. End-users can set the standard on the application testing procedures to ensure it matches their requirement.
Communication is crucial
CIOs say that for an IT initiative, open communications between IT and end-user is vital. Proper and timely explanations of processes to the end-users in a language that they can understand will save a lot of time, energy, and resources on both ends. It will also expedite the results, project timelines, and boost teamwork and trust between them.
