With the boom of IoT, data scientists and businesses are eyeing to capitalize on user-centric valuable data. They are keeping an eye that how IoT, big data and IT infrastructure will change and will provide in the future. There will be a considerable need for a bigger and better IT infrastructure. Along with this, the best-in-class data architecture to convert a massive amount of IoT data into meaningful insights using advanced data analytics.
However, the IoT is going to collect a huge amount of data in the coming years, and this will change the way in which companies collect data, store them, process and how they are going to use it.
5 ways in which a company can handle data provided by IoT to leverage growth:
Reworked Big Data and IT Infrastructure
With a huge amount of Big Data to work on, there needs to be the great IT infrastructure. It will include server clusters, data centers, cloud computing and much more. To do so there needs to be a long-term IT infrastructure plan. With the huge influx of data, companies will have to make sure that even before applying analytics. Also, the data must be structured and organized by the system itself, and that’s the need of data infrastructure.
From consumer companies that gather data from wearable or mobile devices to enterprises that process industrial data, everyone have to go through regular upgrades. The services like Hadoop will play a crucial role here. Apart from it, data centers have to look towards a distributed approach so that data processing goes tier to tier. This will significantly help with backup, storage, and bandwidth optimization.
How IOT keeps Eye on Actionable Data?
The key to success in IoT is finding an actionable set of data that matters for businesses. With the rapid increase in connected devices that are expected to be around 20+ billion by 2020. In this scenario, three V’s of big data volume, velocity, and variety would have an impact. Large, fast and raw data will be continuously poured by connected devices. Obviously, all these wouldn’t be valuable.
After all, getting valuable data out of huge data in-flow will be the job of analysts. what answers are they looking for from the data and data scientists’ jobs will be to find out how they will derive such actionable data that analysts need.
No SQL Database will be New Tools
With a lot of unstructured IoT data in-flow, it is not an easy nut to crack when it comes to sorting them to get valuable insights. It can’t be sorted using conventional relational database management systems (RDMS). However, a NoSQL database such as MongoDB will be helpful for data scientists.
Huge data means a huge place to aggregate and process it in real-time. Cloud-based platforms like Hadoop, Azure, AWS, and others are going to become the backbone for big data in IoT.
- Software for Processing and Analyzing Huge IoT Data
Once a massive amount of data gets collected and organized, it will have the right software stack and database to analyze them to get desired outcomes.
With a huge amount of raw and unorganized data, it will need to be transformed and organized in a certain way. For instance, by using a Hadoop hive or pig component, sorted in a database, tools like Strom should be placed for analytics. The whole analytics should be strategic with speed and volume.
- Need Data Analysts to get meaning out of the IoT data
There is a need for data analysts to get valuable insight out of structured, unstructured, raw or semi-structured IoT data.
If you are looking for one of such companies who can help you through these all processes to get valuable insights through Big Data from huge IoT and IT infrastructure data in-flow. You can rely upon one of the best Azure Cloud Services in India provided by Bien Technologies. We are Microsoft Partner and have been in Big Data and IoT development. Therefore, we have helped many clients in implementing IoT in the best way.