As more healthcare establishments turn to the Enterprise Data Warehouse as the basis of their analytics strategy, to improve service delivery and manage cost, there is need to invest in a workforce with refined healthcare data analyst skills. Lack of necessary skills in analytics is a major challenge in the healthcare industry that makes it impossible to leverage on EDW. Acquiring these skills is required for the support of a data-driven organization, and this brings several benefits.


Data Analysis
Making sense of the data available in the EDW should be the focus of every analytics team member because a lot of information is generated in healthcare, some of which lack relevant details to drive improvements once analyzed. This calls for a keen look at the set theory, and the ability to filter details through SQL, or a statistical reporting tool, or a combination of both. A good analyst should be able to shift through data to retrieve pertinent insights.
The benefit of introducing this system in healthcare is that it can help in the management of cost. For example, a lot of attention is given to the management of diabetic patients, since this chronic disease requires proper care and medication. Enlisting the services of an analyst in the clinical improvement team tasked to handle this condition, will guard against huge costs associated with mismanagement.


Export, Transform, and Load (ETL) Skills
These skills will help a data expert to take data from one system and feed it into another. EDW requires such individuals to pull information from disparate systems such as human resources, EHRS, and finance. A typical example is where a healthcare facility has an EMR system, a costing system, and a patient satisfaction system that do not interface.
The ETL procedure will aid in making copies of data found in each of the systems, to make the details available in the information warehouse. The advantage, in this case, is that integration of data from various systems is made possible through the ETL process.


Structured Query Language
Abbreviated as SQL, Structured Query Language allows an analytics team member to converse and manipulate databases directly through code. An expert with these skills can write SQL code without depending on a guided interface or intermediary such as the drag and drop tool. This will set them apart from those who rely on Crystal Reports GUI or Microsoft Access GUI tools, to generate SQL for their reports.
Such an understanding will give these individuals leverage in particular areas including;


•    Attaining a rudimentary understanding of querying as a result of access to fine-grained data control through SQL.
•    Ability to explore data that has not been filtered through a predefined data set or model, using a Business Intelligence (BI) tool.
•    No information from whichever source is withheld from one's knowledge


Using Visualization For Interpretation
Members of an analytics team should be in a position to interpret the details embedded in data, considering that BI reporting will only avail information in bits and pieces to give you a micro view. Interpretation, in this case, entails the provision of a logical flow that brings together multiple meanings, to create a story or what you could term as the bigger picture.


A practical example of how this skill can be applied in the healthcare sector is where data experts tasked with reporting on A1C testing, blood pressures, eye exams, and foot exams scour databases, to establish possible ways that A1C results are represented in the EDW. You can also perform the exercise on all the tests, to reap the benefit of identifying patients with care gaps such as those who have missed A1C testing, eye exams, foot exams, among others.


As a result, a healthcare facility with such a workforce will make better sense of how it is managing diabetic patients, through evidence-based medicine. It will also help in the evaluation of both clinical and financial outcomes, for an analytic team member to understand the business they support.


 Data analytics skills play a major role in helping healthcare providers to unlock the potential of their data, by turning it into actionable information for a radical change.