Big Data Trends For Q2 In 2017

Big data isn’t only restricted to workplaces today — it’s finding use in some innovative ways. 2017 promises to be an exciting year, and as Big Data is easier to obtain, it presents both some exciting and challenging times ahead. Will you be ready?

Here is a first look at what you may expect to see this year:

  • When it comes to Big Data, organizations are now looking at alternatives to the previous expensive solutions.
  • Used widely till now, Hadoop is being replaced or paired with alternative solutions like Apache Impala, and Hive LLAP, which are better tailored for machine learning, a direction we expect Big Data to be heading off to.
  • A primary trend has organizations going in for self service in Big Data. Even if you’re using Hadoop, the challenge remains to make this data accessible to business users within the organization — users who aren’t data scientists. Many are looking up at services like Alteryx, and Trifacta — the early entrants in the category to make the most of the captured data.

In spite of the changes, Hadoop still remains an important part of the Big Data process.

However, these aren’t the only changes that we should expect to see this year. Here is a look at some of the other ways how Big Data will shape up in 2017. Will you be ready? Read our guide to help you consider and plan your Big Data business developments.

1. Cloud Analytics Help Change Human Interactions

The Transportation Industry

We might see Big Data in the transportation industry more than ever before. Hong Kong Tramways Managing Director, Emmanuel Vivant, for instance, recently pointed out that sharing live tram data with passengers helps reduce transit and waiting time, as well as encourage them to use the tram service more.

Israel and Big Data

Using Big Data seems to be the way to go forward when it comes to managing traffic in the future, and countries like Israel have already started to experiment with it. The 3-mile fast lane on Highway 1 between Tel Aviv and Ben Gurion Airport, for instance, has a toll system that charges passengers according to congestion level.

The higher the level of traffic, the more the fee — ensuring that the State doesn’t just earn higher but manages to keep traffic levels to the minimum too.

TfL and Big Data

Transport for London (TfL) has been using Big Data as well, and has developed a picture of how travel patterns work across their network. In the next quarter we will see a lot more development here, as institutions like the TfL continues to carry out trials to see the best way forward.

2. AI Will Help Find Us Find the Answers We Need

Scientific Discoveries

It’s not only the transportation industry that benefits from big data — recently, scientists developed a procedure to identify whether any child will suffer from autism through a simple blood test.

And they did it all with the help of Big Data, which helped them see through the different patterns. According to Digital Trends, “For the work, investigators measured 24 different metabolites in a blood sample, and then used big data techniques to find patterns tied to two connected pathways that have been theorized as being linked to ASD. By using big data, it was possible to establish patterns that may not otherwise have been discovered.”

Deep Learning Gets Better

Artificial Intelligence is a lot closer to reality than you might think. As Mark Zuckerberg states on AI, it would be as little as five years before we would see machines overtaking humans on many tasks, like when it comes to acting as a customer service representative.

Deep learning algorithms are much more advanced today than before, as Zuckerberg’s Jarvis, would tell us. With deep learning algorithms, you don’t feed a particular answer to the machine. Rather, you give them an instruction, and they will search from all the information they can find, to tell you the best possible results.

It’s pretty much like what Google Assistant does when you tell it to tell you about the weather. And they’re getting a lot smarter now. You could experience the smartness with Amazon Echo, for instance. It can do a whole lot including booking a cab for you.

The complex versions though, can do a lot more, like finding new algorithms that humans could not — often using patterns and methods you wouldn’t think of using as a human.

3. Hacking Remains a Threat

Big Data and IoT are related in more ways than one, and there is an urgent need to check if your organization has adequate security.

  • Last year, we witnessed the first major IoT DDoS attack on the U.S. East Coast, which brought down thousands of connected devices.
  • For hackers, it could be easy to gain access to Big Data through IoT devices, and there is still little you could do about it.
  • It’s estimated, for instance, that ransomware threats increased by as much as 6000% last year!
  • Apart from external threats, comes the problem of restricting workflow data within the organization as well. You’d need to ensure that not all information is viewable by everyone, and you’d need a proper system for that.

4. Better Organizational Management and Employee Productivity

Now, let’s take a look at how organizations stand to benefit from Big Data in the second quarter this year. While Big Data has been traditionally used to make better business decisions by C-level executives, the environment would be a bit different now.

The problem is, employees often do not have the right data or input to help them make quicker decisions. It’s employees who have to make real time decisions most of the time, and informed decision making can help cut costs and losses to a great extent while improving the overall efficiency.

Big Data can help solve that problem, as it can offer employees real time data, including getting access to information they need and identifying any errors.

Our Take on Big Data in 2017

2017 is going to be the year where we have finally warmed up to a world with Big Data. It is still the early days of Big Data adoption, but industries and institutions from around the world realize that it’s the way to go forward. Add to it the fact that AI today is a lot more advanced than what we would have thought possible even a decade back — then the next decade truly brings some exciting possibilities! What are your predictions? We’d love to know

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Originally published at blog.100tb.com.

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