Aureus Insights

Big Data and Analytics Trends 2018

Written by Aureus Analytics | Jan 08, 2018

2017 has been a year when ML/AI technologies have become mainstream, and businesses are conversant with their application and possible use cases. 2018 will, however, be the year when trends from 2015-17 will finally come into maturity and we will be able to see results. Commercial application of blockchain (beyond Bitcoin), wider acceptance of enterprise SaaS solutions, and optimization of investments in data lakes – are just some of the examples we can think of. Customers too, are now beginning to understand more about data privacy and security, and want to be more in control of their own data. It seems that finally in 2018, technology and business will move ahead together.

The highlights of 2018 will be as below.

  1. BLOCKCHAIN BEYOND BITCOIN: Since the introduction of Bitcoin in early 2009, it has become the poster boy for all things blockchain. So much so, that often, they are interchangeably used. 2018 will finally see the de-linking between the technology that is blockchain, and its applications. We anticipate that blockchain will find a application in other areas of financial services such as smart contracts, insurance fraud prevention, anti money laundering, just to name a few.
  2. TIME FOR DATA LAKES TO PAY UP: The last few years have seen significant investments in data lakes. Enterprises decided to move part of their data warehouse investments into data lakes in order to promote enterprise wide usage of data as suitable to each function. 2018 and onward will see a slowdown in these investments and a greater ask of the ROI.
  3. FAST SMART DATA OVER BIG DATA: No, this does not mean big data will no longer be in focus. It does however, mean that attention will now shift towards fast and smart data. That is data which is in real time and useful and usable for a specific use case. While having ALL the data in the enterprise handy for analytics is great, it may not serve any purpose if the right data set is not used properly for the right problem.
  4. PRESCRIPTIVE ANALYTICS FOR ALL: In enterprises, data science and analytics have been used mostly to forewarn of potential outcomes - 'what could possibly happen' scenarios. Stepping into 2018, these advanced technologies will play a bigger role in active decision making - 'what to do / what action to take and why' scenarios. The visibility of the 'why' rationale is going to be critical.
  5. DECISION AUTOMATION: Strategic decision making to a large extent will become fully automated. Artificial intelligence and machine learning will drive action without manual intervention. No, we're not saying that robots will completely over take, but smarter software will become more prominent. Decision automation will be visible across all functions right from the CEO's office to the day to day operations.
  6. CONSUMER GRADE ANALYTICS: Analytics so far have been restricted to enterprises and their data scientists for basing decisions for customers. Stepping into 2018, we see a lot of customers seeking out tools that help them get answers from their data. A lot of these tools may come from players who are currently building enterprise tools for data analytics and visualization. Consumer grade analytics will be a trend to watch out for in 2018.
  7. BE SENTIMENTAL: Customer experience has never been as important as it is now. Organizations want to capture customer feedback at every interaction and transaction. Sentiment will plan an increasingly significant role to help companies decide the next best course of real time-based parameters such as location, demographics, life stage, etc... 2018 will see an increased adoption of customer feedback analytics tools.

So these are the highlights we see for 2018. Customers want to be in control of their own data, and with that, technology will move more towards that direction.