Big Data Transformation Programs !!
Across industries, “Big data” and “Analytics” seem to excite and empower businesses with quick insight into current business situations and indicative business performance using predictive analytical models. It’s almost like holding a crystal ball under the mouse!! This surely is exciting business users who can now at any point of time take stalk of how their business strategies are performing rather than wait for quarterly reviews based on complex feeds, excels and all time favorite pivots….
However using Big Data Analytics to its true potential is quite a daunting task and requires laying down a detailed roadmap
Listed below are the top 3 challenges in Big Data Transformation Programs :
- Data
Data, Data and More Data…and More Data!!
This can be quite a harrowing task. A plan to first identify the Data required for the Transformation program is of fundamental importance.
Manufacturing and Pharma companies mostly have their critical data residing in legacy and ERP applications. There are multiple Data warehouses or Data Marts scattered within the organization. Additionally information may be structured by business functions or running horizontally across business units.
Semi Structured data like payment gateway data and Unstructured data like chats and social media data floating across the web add to the complexity of Data capture and process. With the companies now experimenting with Digital and IOT based solutions planning for appropriate data capture, process and storage is of prime essence
This calls for data rationalizing, redefining the data architectures, redefining business process, implementing data governance, tagging golden source data and implementing data security.
This though the most daunting… is an imperative foundational step to healthy and accurate analytics within an organization
2) Tools and Technology
The next big step is to select between plethora of tools available for big data solutions. They range from open source products to individual licensed products to tightly integrated products sold by large organizations that build Hardware Software Engineered Together.
Additional consideration may be given to data storage by considering On Premise, On Cloud or Hybrid data storage. Data Security and Data Masking tools for key data, gains high importance when looking at distributed storage model
3) People & Mind Sets
There’s no substitute for serious engagement and participation by the corporate and senior management team in such Transformation Initiatives
Having a detailed roadmap with objective milestones, execution becomes easier. Be it integrating data, conducting proof of concepts, training the teams in the context of a clear vision is very important
This also requires Aligning Investment with Transformation Milestones
Empowering the Frontline employees and managers to embrace technology becomes imperative in order to make effective use of analytics.
Collaboration is the key to securing commitment, reinventing processes, and re-aligning organizational behavior for a successful Big Data Transformation Program !!
