Businesses can only thrive successfully when all stakeholders are equally excited about data analysis as the analysts in the team. For an organisation to be data-driven, Analytics must permeate as a value within the organisation. Understanding data and using the results to drive business action is only a good idea.It is a hotly discussed topic that, although IT aficionados are interested in supporting analytics, they simply do not understand to differentiate legitimate business needs from nice-to-haves, and are frustrated that data analysts don’t understand and appreciate the reasons behind IT practices. One of the most fundamental things that analysts need to do in their job are things like derive raw (not aggregated) data and adequate computing power. Forbes Contributor, Meta Brown simplifies the Data Mining process for all readersul>
Business Understanding:Get a clear understanding of the problem you’re out to solve, how it impacts your organisation, and your goals for addressing it.
Data Understanding:Inspect, describe and evaluate the available data.
Data Preparation:Take data from the state it’s in to the state needed for analysis.
Modelling:Use mathematical techniques to make models (equations or other logic) you can use to support business decisions.
Evaluation:Assess if models are viable.
Deployment:Integrate models into everyday business.
These phases are parts of an ongoing cycle of analytics activity, and the analytics team may work back and forth among these phases frequently.IT has a tremendous role to play in each of the phases, some more than others. Here are some ways that IT can and should be involved within the Data Analytics framework of your organisationul>
Getting access to the most relevant data in the most appropriate form clearly calls for involvement from data owners and gatekeepers.
Integrating models into operations is almost always out of bounds for analysts; they must work with IT to make those changes.
More subtle IT input happens in other phases, like modelling— IT staff generally don’t have the skills needed to develop mathematical models, but they may have important expertise to offer about what business process changes are, or are not, feasible.
The information provided by IT professional guide analysts work within a framework that they can use to determine the kind of models that may or may not realistically be deployed in the businessstrong>
