By Ashish Tanna
2017 has been a year when machine learning (ML) and artificial intelligence (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 resultscommercial application of blockchain (beyond Bitcoin), wider acceptance of SaaS solutions, and optimization of sunk investments in data lakes. 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:
- 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 delinking between the technology that is blockchain, and its applications (such as cryptocurrencies, one of which is Bitcoin). We anticipate that blockchain will find application in other areas of financial services such as smart contracts, insurance fraud prevention, anti-money laundering, just to name a few.
- Time for data lakes to pay up: The last two or three years have seen significant investments in data lakes. Enterprises decided to move part of their data warehouse investments into data lakes to promoter enterprise-wide usage of data. 2018 and onwards will see a slight slowdown in such investments and a greater ask of the returns on these investments.
- Fast smart data over big data: This does not mean that 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 relevant data set is not used properly.
- Prescriptive analytics for everyone: In enterprise situations, data science and analytics have been mostly used to forewarn of potential outcomeswhat could possibly happen scenarios. Stepping into 2018, these advanced technologies will play a bigger role in active decision makingwhat to do / what action to take and why scenarios. The visibility of the why rationale is going to be critical.
- 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 are not saying that robots will completely overtake us, but smarter software will become more prominent.
- 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 customer seeking out tools that help them get answers from their data and the onus for that will be on companies that build enterprise tools for data analytics and visualization; tools that will help users leverage analytics in their day to day life, without having to resort to or learn complex tools. Natural language generation will play a big role here.
- Be sentimental: Customer experience has never been as important as it is now. Organisations want to capture customer feedback at every interaction and transaction. Sentiment will play an increasingly significant role to help companies decide the next best course of in real time based on parameters such as location, demographics, and life stages.
Featured Image Credits: CommScope on VisualHunt / CC BY-NC-ND