Candidates with Big Data backgrounds may benefit from being aware of related technology trends where their skills may be better appreciated.
How can the term Big Data be viewed?
Many different technologies and projects can be tightly or loosely related to the “Big Data” ecosystem.
Data needs to be extracted, housed, manipulated, interpreted, and shared. Depending on the size of the company and project, each of these phases can represent different technologies and discussions. Traditional technologies associated with these different phases include data warehousing, data modeling, dash board, performance management, financial reporting, OLAP, and ETL. Some aspects of this continuum include highly technical discussions and others more related to the information needs of business users.
Business Intelligence is most commonly associated with gaining access to data in a way where users can better see what has already transpired relative to sales, profits, human resources, marketing, manufacturing, etc. However, there also disciplines within business intelligence such as “data analytics” that enable the users to interpret or even speculate about why trends are occurring and speculate what may happen in the future. Analytics can occur outside the traditional “business” functions, such as web analytics.
“Enterprise search” has been a popular technology that enables users to apply business intelligence concepts to unstructured content, i.e., web content, documents, emails, etc.
Big Data is often associated with distributed servers to store data in a way that is less expensive and more easily accessible in a rapid manner. It is also represents exponentially greater volumes of data derived from machines, social media, and science (often unstructured content). Big Data tools are designed to interpret the increase in data in a timely manner, often via visualization tools. Similar to Business Intelligence, Big Data analytics can be purpose built for a specific function or industry, or sold as a platform to empower an enterprise to perform many diverse processes.
If you have been selling IT infrastructure solutions, you may be more comfortable selling technology related to the secure storing and delivery of the Big Data; otherwise you may uncomfortable talking about financials with a division controller. Along the same theme, the sales person whose experience is selling to line of business executives may become confused or bored talking to data center executives about virtualization and data storage. Big Data can mean a lot of different things to a lot of different people.
Candidates should be aware of where can they extend their careers across the evolving world of Big Data and Business Intelligence. Be sure to recognize where you need additional technical training or at least read publications that increase your credibility with the evolving vernacular. Awareness precedes the next important step of communicating where you have been versus where you are going. Communicating without initial thought and awareness sounds like senseless babble or generic blah; conversely, awareness without communication is a waste.