In Demand – Data Analytic & Reporting Skills

I recently came across a number of articles on the latest hot skill “Data Analytics”.

With the explosion of information in recent years, companies are under severe pressure to capture opportunities ( increase revenue, profit, efficiency and customers) within a limited time period. This has resulted in a substantial increase in positions responsible for data analytics in order to convert massive amount of information (user behavior trending, adoption, etc.) into meaningful data.

By focusing on the technology know-how or purely number crunching abilities, companies might not reap the benefits of hiring additional head count. The ideal hire profile should include good understanding of business operations and processes in order to translate the data into insights.

There has always been a need for people with good analytical skills who can transform information into meaningful strategies for the business to pursuer revenue/cost reduction opportunities…This skill in most cases cannot be taught in school or by courses offered by a number of institutions. This comes about by having hands on experience and innate curiosity and interest in the big picture.

Tips to those who are embarking on this career path, (1) focus on big picture (2) focus on interpreting results and presenting them from a business case (3) technology often changes, methodologies and sound logic rarely do…

For companies, embarking on business intelligence / Data warehouse solutions, focus on business needs and understand your current reporting capabilities and see if your current staff can support the current and future requirements…a new tool might not be productive by itself…a focused training / learning session on adopting best practices in data analysis and reporting might be of great benefit to your current employees and enable them to grow professionally.

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

What is the impact of poor data management?

• Reduced customer satisfaction due to incomplete, out-of-date or incorrect data
• Inability to bring new products to market quickly
• Depleted or overstocked inventory
• Loss of revenue due to billing errors and lost opportunity
• Lost manufacturing time due to inaccurate parts ordering
• Regulatory fines due to noncompliance.

the list could go on and on, these bullets are to give you a sense for the need to better manage data!

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

What is Data Management?

There are two popular definitions:
One from DAMA
“Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise”
Another from DMBOK
“Data management is the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets.”
Companies of all size have to manage their data in order to meet their customer’s requirements in a timely manner.

Industry specific definitions

In the medical and pharmaceutical communities, Data Management is a term generally used to describe analysis of database information which has been collected during clinical trials. It also is used to define how data is identified, collected, and analyzed to establish clear evidence of outcomes.
In the modeling and simulation world, Data Management is described as "model-based", and is defined as planning organizing, and managing of data by defining and using rules, methods, tools, and respective resources to identify, clarify, define, and standardize the meaning of data as pertains to relationships.
In the information technology arena, DM is defined as a type of client/server computing where some portion of the application data is executed on two or more computers. It is also described in its IT application as control of data handling operations – such as acquisition, analysis, translation, coding, storage, retrieval, and distribution of data – but not necessarily the generation and use of data.

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"

Data vs Information

Data are plain facts. The word “data” is plural for “datum.” When data are processed, organized, structured or presented in a given context so as to make them useful, they are called Information.
It is not enough to have data (such as statistics on the economy). Data themselves are fairly useless. But when these data are interpreted and processed to determine its true meaning, they becomes useful and can be called Information.
Example:
Data is what you collect, for example you may collect a sample of heights, ages, genders within a given geographic area.
Information is what you extract from that, i.e.: average height by age, or average age by postcode.

Data Management is a critical part of business strategy as it is responsible for the transformation process of data into information. Information is the lifeblood of a business; its health is vital to an organization and is fundamental to your success and competitive edge. Good information reduces uncertainty surrounding decision making, and contributes to aspects such as improved productivity, compliance, and more focused marketing and customer loyalty.

"Disclaimer: The views and opinions expressed here are my own only and in no way represent the views, positions or opinions - expressed or implied - of my employer (present and past) "
"Please post your comments - Swati Ranganathan"