In 2014, enterprises advanced their big data initiatives by converting plans into working projects and even implementations of big data that have transformed the business. In 2015, these businesses will know much more about big data, and what it can and cannot do. Unsurprisingly, many will create their 2015 budgets based upon what they have learned.
I predict the trends for big data in 2015 will be a combination of strategic and operational goals, headlined by the following major areas of focus. Let us know in the discussion what you think will be the hot big data topics in the coming year.
Reemphasis on systems of record (SOR) systems
Now that volumes of big data have piled in to corporate storage, enterprises are struggling to get their arms around this data, and to discover which data is useful and which is not. The only data that is useful is data that can provide answers to key business questions.
Enterprises have discovered that the best ways to vector into this data is by using the access keys of their traditional SOR data for queries. In 2015, there will be a concentrated enterprise effort to link SOR data into big data repositories as a means of navigating through the data and finding the “pearls” of corporate wisdom.
A new emphasis on data collections
The profession of collecting and organizing documents and information began around 1200 BCE. Enterprises will be discovering the importance of librarians all over again in 2015 when they realize that they can’t keep every single byte of big data that flows in, and it becomes time to establish meaningful “collections” of big data that are useful to the company. Data analysts with library skills may be needed to do this.
Whether it is data analysts, business analysts, data scientists, or a combination of all three, the art (and science) of data curation, centered around organizing collections of data that will support the present and the future, will be integral to the effort.
More real-time data
In-memory analytics capabilities and insistence from business for immediately actionable information will continue to push big data efforts into real-time instead of batch reporting modes. Two of the most prominent real-time big data applications in business are online retail (and consumer buying patterns) and supply chain management that enables managers to respond immediately to supply chain blockages such as a supplier failure or a disaster that impacts supply chain flow in a specific geographical area.
A business continuation plan for big data
Thus far, corporate disaster recovery and business continuation plans have focused on the recovery of SOR data that support transactions that drive orders, accounting, material management, etc. As big data moves into real-time system scenarios that the business will rely on for its present decision making, big data will also require a formal disaster recovery and business continuation plan for applications, storage, and processing.
Assessment of where the cloud plays in big data
Because of system latency and corporate governance issues, a majority of organizations are running their big data applications in-house. But for reasons of business agility and business continuation and disaster recovery, they might opt for some off-premises support of their big data and applications going forward. 2015 will be the year when the big data architecture discussion “opens up” into scenarios that one day will encompass both on-premises and cloud-based big data support.