Analytics and Big Data: What's In Store For 2016?
Disruptive technologies saw an all-time rise in the year 2015, as they actively became a part of day-to-day conversations owing to government initiatives like Smart Cities and Digital India. Yet, while they were discussed dynamically, some of them did not see as much adoption in reality.
In 2016, these technologies are bound to be spoken about again, and with that comes the promise of adoption and opening of the mainstream path. This is made more certain with increased awareness and adoption in the market. Some of them being:
1. Cloud Analytics
Late last year, cloud analytics was just a buzzword which will drastically change next year. The amount of benefits cloud analytics provides in terms of cost reduction and efficient resource utilization will drive more and more CIOs to look at it. While adoption has been slow by individuals, enterprises and SMBs have taken to the cloud with a gusto. They continue to become more data oriented allowing the market to grow rapidly, providing a whole lot of opportunities for a company like ours. This growth will be driven by trends like cloud analytics. The cloud has been the primary source of innovation in the year 2015, and will continue to be an important source for technological development for the next year, as well as years to come.
2. IoT, Cloud and Big Data come together
The technology is still in its early days, but the data from devices in the Internet of Things will become one of the “killer apps” for the cloud and a driver of petabyte scale data explosion. For this reason, we see leading cloud and data companies such as Google, Amazon Web Services and Microsoft bringing Internet of Things services to life where the data can move seamlessly to their cloud based analytics engines.
3. Mobile analytics stands on its own
Where in 2015, products with a fluid, mobile-first experience began to emerge, working with data out in the world is going from being a chore to becoming a dynamic part of the analytics process. In a world where devices are always connected and where your data increasingly resides in the cloud, words like “mobile” and “cloud” cease to matter and it simply becomes about answering questions quickly and communicating results.
4. Visual Analytics becomes a common language
Data is becoming an increasingly common tool, with more and more people becoming more and more comfortable using it every day. People are visualizing their data to explore questions, uncover insights, and share stories with both data experts and non-experts alike. As data usage grows, and more people turn to data with both professional and personal questions, employers are also beginning to look for employees who think critically with data. In this, visual analytics serve as a common language, empowering people to reach insights quickly, collaborate meaningfully, and build a community around data
5. New entrants in the BI ecosystem
There are a number of new technologies in the BI ecosystem. As these go to market, we’ll see gaps that need to be filled. There will be new companies to do just that. Hadoop accelerators, NoSQL data integration, IoT data integration, improved social media—each of these provide an opportunity for a new company to start up. In 2016, we’ll see the rise of the gap fillers, leading to a market consolidation. And organizations will continue to shift away from single solutions and embrace an open and flexible stack that includes these new technologies.
Till some time ago, all these technologies were being adopted by enterprises in isolation. The trend that is already emerging and will really take off in the next year is an integrated use of these technologies. With the rise of digitally born companies like Uber, AirBnB, Paytm, etc. traditional business models have woken up to the importance and need of these technologies. The adoption of these technologies will touch new heights in the year to come as every organization wants to and has to digitally transform itself to stay relevant and grow in the current market.
Though these changes and trends may seem disparate, they’re all linked by the need to work with data quickly and conveniently. As Big Data changes and new ways of working with that data pop up, the details shift, but the song remains the same: everyone’s a data analyst, and there’s never been a more exciting job.
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