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Where is Big Data headed?

Organizations will opt for database technologies that provide analytics at the same speed as their main business (i.e. processing large transactions at extremely low latencies and allowing in-memory analysis/ decision making.)

The ability to achieve cloud-like flexibility in the enterprise data center with commodity x86 servers, DevOps practices, and software based application services will enable businesses to maximize Big Data performance and scale.

You should see more tools available for small businesses to self-prepare their data for analysis, since Big Data is now trickling down from larger corporations as a way to make better business decisions.

The primary change is prescriptive analytics expansion — in streaming, security, impact on lifestyle, better governance to cure the Big Data excess-collection bellyache, and cleaning up faulty open source algorithms.

We’re already seeing cross-platform ads – search the Amazon mobile app, and then see the product again in your browser-accessed Facebook. Big Data will further enable more sophisticated re-targeting and pre-targeting.

As demand for high-fidelity enterprise Big Data brokers continues to grow rapidly, traditionally paid services will become free to capture more structured data about end users.

2016 will be the year for small business in the world of Big Data. Advanced
technologies that at one point were only available to the enterprise are now analyzing Big Data for long tail SMB’s. The subsequent transparency will level the playing field for small business in a big way this year.

The ability to explore and discover insights will move closer to the source production data stores and in many instances the production store will also act as the analytical platform.

The biggest change will be how Big Data is leveraged to advance business goals. Big Data analytics in the APM (Application Performance Management) arena will now gather not just data but actionable insights.

The future of Big Data is in industry-specific strategies. Can you accurately predict when a meeting room is available? Or who will come? Or the best way to get there?

As businesses stop worrying about whether Big Data provides business value, they will rightly focus on ensuring that the data that powers these applications is always available and always protected.

Data as a Service (DaaS) built into data-driven applications will dramatically change the game, not just for acquiring external data, but for sharing data internally and providing the opportunity to monetize data through outbound licensing.

Companies will outsource Big Data to the cloud, as cloud providers will leverage APIs and cloud-to-cloud integrations to deliver insights from systems of record.

In the next two quarters there will be a huge upswing of cloud service providers pushing Big Data as a service for their customers. There will surely be a significant price cut to make Big Data tools available for the average coding shop.

Big Data prediction can help us find out what thought patterns are not serving us or limiting us and how to find the best activity to help the individual change his/ her patterns.

“Big Data” will become “Huge Data” with data streaming in from the “Internet of Things”. Advances in hardware devices & software tools will spew a new generation of productivity for humankind.

How the television industry handles data will change. Forget ratings. New data provides more accurate ways to determine financial success — such as which items were bought inside a show.

Big Data tools will continue to become easier to use for those that have little coding experience with drag & drop capabilities, making Big Data more accessible.

2016 will be the year where a paradigm for virtualizing Big Data infrastructure will become established as part of the journey towards adoption by mainstream enterprises.

Cloud providers will increasingly benefit from Big Data. The unlimited availability of storage and processing power that cloud providers offer is too attractive for organizations to ignore.

Big Data is a Reinforcer, Not a Replacer. One student might take four years to complete a college degree and another six. Data doesn’t consider the why factor.

11 Comments

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  1. The response to the question “Where is Big Data headed?”, well the appropriate answer will be “Very Far,by spreading across every domain of human kind”. Big data has started ruling the 21st Century,the demand for analysts who can analyse data from larger chunks are in more demand.Every field,every domain requires data science,be it BCCI deciding which player to selected in the team according to their performance in the Domestic cricket matches or maybe a company looking for a new industry to invest in.BIG DATA is everywhere and rules the functioning of these domains. As told above cloud computing companies might trade for Big Data and vice versa might take place.Well from the recent development of technology Big Data has made its way to integrate itself with any technology available.It keeps the capability to develop that technology as well as grow with that technology.In a country like INDIA Big Data should be utilized to determine how to help the under-privileged and to find out how to meet the demands of the population present Below Poverty Level.This can help in providing faster solutions and also dealing with problems quickly.

  2. The real value isn’t in storing the data; it is about interpreting the data so that it can be put to work. The Zendesk acquisition better reflects the path of where Big Data is going and how it is going to get there.

  3. Big Data has made enterprises rethink their business models and dive into a “Research Mode” to find new and better ways to solve a particular problem. They are forced to innovate and this has given a rise to a very long list of new technologies being developed in and around the Big Data space.
    Big Data is massive and there are many facts backing it. We are seeing in-memory computation technologies, integration of cloud, virtualization, rise of Docker, BDaaS (Big data as a service). All these seem very exciting and we can see the avenues these technologies are paving way for and they can surely be considered as the future of Big-Data. While these are just the technological advancements caused by Big-Data but there’s still more to Big-Data.
    The main story unfolds when we start looking into Big Data, the scope and opportunities are very high. Big Data combined with ML can do wonders and it has been seen in today’s world. Be it the Mobile personal assistants, smart applications, self driving cars, targeted marketing, Google’s AlphaGo, things as simple as a google search and facebook friend recommendations are also wonders of Big Data and ML. And there are many many more to this list. We feel amazed when we think about these innovations but we haven’t seen what is yet to come. One thing for sure though, It would be BIG!!

  4. Big Data has very bright future. But its important that instead of using it only for commercial purpose. Can we use it better so that it can actually humanity and not just provide profits to enterprises. There are various area where Big Data can be a boon.

  5. Big data presents lot of opportunity and comes with lots of con and pro and relevance factor always arises as trnds with growth of Big data technology. And matter of concern will be like “big data is better data” ,” what are the ways to Monetize The Data”and more importantly “Privacy of data” .

  6. with the advancement of technology at every step i personally feel that what big data at present needs to focus is upon its privacy handles as to get done with security issues greatly……… rest what it has committed to till yet is amazing

  7. As more and more young tech-entrepreneurs emerge and size of data available keeps on growing, there will be emergence of product based analytics company specially those who provide cloud based products. This makes economic sense for start-up companies as they lack sufficient funds to spend on infrastructure require for big data and also the expertise for the same. Cloud based product companies can provide them data infrastructure as well as the data and also the expertise at competitive pricing which traditional service based analytics companies can’t provide although there is general shift even in traditional analytics firm towards Product-IP based analytics solution

  8. The balance is slightly tipped towards the positives of big data such as the emergence of innovative business models although some significant downsides are raised around privacy and whether it will cause more problems than it solves.

  9. Big Data predictions can make or break the foundations of a start-up and it is extremely crucial to analyse the Big Data well . Statistics determine the validity of a business plan and these can only be determined after having proper software for filtering the Big Data. The biggest challenge of 2016 is going to be development of such advanced systems.

  10. The pre-targetting and re-targetting concept by Ms Windy Fox ticked me.Because evryone of us has experienced it.We download an app and the another app and many a times we observe similar things.It shows how are data is being used for predictive analysis.

  11. one threat that poses till now are security issues. if the advancement of big data can tackle the spread of this technology is very much inevitable. interesting way to present information.

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