Since the last couple of years, we have experienced revolutionary changes in the data analytics arena. Big data became main stream and Data Scientist got termed as the sexiest job. Data explosion has come with its own fair share of challenges and opportunities. As the businesses are looking forward to monetize the data, they are grappling with finding suitable business use cases to leverage and execute on the new data platform. Added to this is the trouble of finding skilled workforce to address the burgeoning demand.
Recent Alteryx research report has found that 72% of the business leaders are not satisfied with the speed at which insights are derived from data and nine out of ten dissatisfied stakeholders blame others on the inability to blend data from various data sources.
What to expect?
Segmentation of Vendors – Industry is fast gyrating towards three categories of vendors who are providing technologies that assist the data analytics life cycle viz. Data Platform providers like Cloudera, MapR, Hortonworks etc., Data Wranglers such as DataRPM, Tamr etc. and Guided Data Discovery providers like Alteryx, Datameer, Databricks etc. Adding interesting twist to this mix is the new age big data visualization vendors like Platfora, Tableau etc.
It’s something of an irony if you find striking similarity to the data world where we used to live in until recently which was dominated by Oracle, DB2, MS SQL Server etc., as Data Storage providers, Informatica, Datastage, Abinitio etc., as ETL providers and Cognos, Business Objects etc., as the vendors for BI / visualization.
Few other distinct trends which we would emerge in days to come would be:
- Machine Learning would become main stream
- Deep learning could fast replace machine based learning technologies
- Most of the predictive modeling and data science could become code-less or automated
- Everyone would become data analyst or at least would be able to do sophisticated analysis through the power of these new found tool sets
- Data blending would become main stream and rapidly get commoditized – a real threat to Big Data based analytics
- Adoption of real time streaming and analytics would be higher – expect Apache Storm and Spark to be heard more often than before during your discussions
- Signals based approach would become more prevalent than the atypical use case driven analytics approach where advanced analytics would be driven by a library of domain based signals. We already see companies like Opera Solutions, Platfora, IBM’s Watson etc., taking lead in this space.
- AI / VR could become an integral part of the strategy for the forward looking organizations
- Graph databases would be increasingly used as the new destination repository for guided discovery / analytics
- CIOs would have minimal say on the choice of analytics / tools / methodologies which would be driven by the business through the newly created roles like CDO (Chief Data / Digital Officers) or CAO (Chief Analytics Officers)
How many of these trends have you seen already kicking in? Or have I missed out something more critical and significant? What do you think?
Please share your thoughts.
Let’s ask bigger questions…
Image Credit – Morguefile