Imagine with me for a second that “smart” isn’t just applied to phones. Instead, imagine a world full of smart devices that communicate with each other at all times. Imaging smart houses, tables, or even clothing that can track where you are and what you need.

This is where we’re heading and it isn’t too far in the future. The internet of things is the communication of devices wirelessly that connect objects or people to the internet and create a stream of data.

And the Internet of Things is already here. You can look at devices like Fitbit or Apple Watch that have had huge success. Now we know that by 2020 there will be about 50 billion smart devices in existence. If you thought big data was already too big to handle, it’s only going to exponentially grow from here.

When it comes to capturing targeted, high-value data sets; data scientists will be in high demand. But how much bigger will this data actually get and what changes will this cause?

Here are five ways the IoT will affect big data and big data barriers.

1. IoT will enable the capturing of more actionable data

How do we turn big data into actionable data? That’s the question many big corporations have been working on for many years now. Now that we can control the streams of data coming in to us from IoT devices, managing all that data will become easier. Managing it with a clear goal in mind and with data specialists will lead to actionable insights.

Many companies including Salesforce believe organizations will have higher return on their investment in the future though big data due to these actionable big data insights.

1.  Marketers can change their message to meet exactly what product users want. In a similar manner, product users can give immediate feedback to brands.

2.  Businesses will now have more information to know exactly where prospects are in the buying process, thus allowing them to send them the right message at the right time.

3.  Product upgrading and replacing will be made seamless. Now that devices are becoming smarter, they will be able to send data to companies letting them know when they need to be replaced or need a new part.

4.   Social networks and IoT devices will be connected. Marketers will now have more opportunities to communicate with brand followers and mine data to find new trends.

5. Irrelevant and untargeted advertising is becoming less common. The wealth of knowledge about users and how users put products to work will become holistic. Advertising and marketing will now match user’s exact interests and behaviors.

2. More data streams mean organizations will need to adapt their IT departments and data centers.

IoT data analytics will rely on the power of the IT infrastructure that companies have to offer. Cloud computing and data centers will need to be invested in to be able to handle to pressure big data analytics is capable of creating. Aggregating and organizing all that data is the first step to analyzing, and this is impossible without powerful capabilities.

The data can be coming in from purchased data set from aggregators, from mobile devices, or from wearables, it doesn’t matter. Data centers will need to be upgraded regardless. Apache’s Hadoop and other platforms have been introduced to handle this influx of data.

We foresee data centers taking a new structure altogether as well. Smaller data centers will aggregate data from connected devices then transfer that to larger clusters to be analyzed.

3. NoSQL databases will become the most popular

Because many devices that are part of the IoT are unstructured, relational databases have a hard time dealing with it as opposed to NoSQL. The many different NoSQL databases out there have been created for easy data organization that holds an ever increasing importance in the big data field.

Pulling in more data means we must have places to store it and organize it. Many companies like Microsoft spearhead this initiative through Azure that can handle it in real-time.

4. Companies will need to choose a service to process and analyze all IoT data

Now that more data than ever will be coming in from new IoT devices, companies will be forced to either be prepared or to lose an advantage. They must choose a software service to handle these databases and process the data.

Companies must look into how they plan to turn raw data into actionable insights through tools like Hadoop. Combining Hadoop and Apache Storm can combine to form powerful tools but there are plenty of options out there to choose from.

5. The demand for skilled data analysts will be harder to fill

The demand for data scientists and data analysts has already risen significantly, but it only set to skyrocket in the coming years.

But to really put your data to work, this is a requirement. Data must be translated into valuable insights, especially for larger companies. So building this department up now rather than later might be a wise investment.

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