How would big data evolve with the adoption of IoT in business
Big data is a relatively old concept which has its broad application in business. But the Internet of Things (IoT) is relatively newer, and as per estimates, IoT will add $10 to $15 trillion to the global GDP in the next two decades. You may or may not be having an activity tracker that can communicate with your smartphone or the lights in your home may or may not be controlled remotely through your smartphone, but IoT will substantially affect your lives soon. Within three to five years you will surely have one of these gadgets with IoT transforming your daily life to a great extent. These predictions are not made based on the fact how cool these products are, but an even more intriguing point is that Internet of Things is sure to change the business at the fundamental level very soon.
How will IoT change the business world?
You may be wondering that an internet-connected frying pan or a smart tennis racket is rather stranger versions of appliances we use, but the market will decide which devices and apparatus would be internet enabled and smart. Eventually, we are advancing towards a more connected world where more intelligent and interconnected devices would exchange data to provide services that would improve the quality of our lives. Apart from this, interconnected and smart objects would have smart sensors embedded in them which would allow them to send and record data back to the cloud.
Whether it is self-driven cars or aircraft engines, devices and machines would be smarter to send real-time data and receive instructions in real-time for better efficiency. These smart devices would help organizations to collect and collate information to identify user behavior patterns better or to devise future products. IoT would allow product manufacturers to understand the behavior patterns of users so that they can understand which features of the product are more popular so they can focus on them.
Not only devices and products, IoT will enable businesses to collect information from all areas of business, change their business models and processes and improve productivity. With the widespread application of IoT, we seem to land up in a much smarter world with smarter roads, cities, cars, and infrastructure. Different business models will inevitably evolve, and many companies will start helping their customers with data and information which would dramatically transform the customer experiences and expectations. Internet of things would pose to offer a fundamental tilt in the way we look at the world at present. In the very near future, most of us won’t prefer to go back to a phone which is just a phone or a device with a single utility. In the same way, we won’t be possibly able to imagine a world without a smart car, road or infrastructure.
The Data Revolution
In traditional businesses, data used to be generated and collected through the value chain like the operational processes, interactions with customers, vendors, and suppliers, order processing, customer service and so on. With the Internet of Things, these traditional sources of data are supplemented by the smart and connected products themselves. The advent of IoT has helped data to be a decisive asset for any enterprise as raw data are generated, sent, and are analyzed which brings the promise of hair breathed precision to decisions.
Use of Big data
Furthermore, when the product data is combined with other data like commodity prices, inventory metrics, and locations, service histories, etc., the value of it increases exponentially helping businesses to build newer business models and innovate newer products based on real-time data. Thus, as data slowly becomes the main source for winning in the competition, management of it along with its analysis, governance, and security becomes paramount.
This is where Big data comes in handy which is capable of handling raw and unstructured data and pull insights out of it. Big data blends computer science, business analytics, and mathematics to process such huge amount of data and arrive at the decisive insights that businesses need. It employs a family of different techniques to gauge and understand the patterns in the data structures to arrive at conclusions and inferences. As conventional techniques like data analytics using database tables and spreadsheets are not viable anymore owing to the volume and nature of the data, a data lake is used as the repository of data which are of different formats. The data is then studied from the data lake with a set of data analytics tools which can be used for descriptive, diagnostic, prescriptive, and predictive purposes.
Changes of Big data with IoT adoption
Predictions state that by 2025, 75.4 billion connected devices will be around which will be exchanging data and information. This inevitably means that volume, velocity, and variety of data will exponentially increase calling for better data infrastructure, data centers, cloud-based computing, and data clusters. Businesses which propose to use IoT have to invest in IT infrastructure planning as the existing infrastructure won’t be able to withstand the load of such high influx of data volumes which needs to be processed. Even before the data scientists start exploring the data and apply analytics to it, data needs to be organized and aggregated. With the increase of the volumes of data being processed, the data centers will have to comply with a more distributed approach with different tiers of data storage in mini data centers. Certainly, this kind of approach will have an effect on data security, storage, bandwidth and the procedure of backup.
As volume and variety of data increases, the key will be to implement technology and data science to find actionable data from the vast data repository. The business analysts will have to find ways to sieve this data and define the question they want the data to answer. The data scientists will then look for ways to find those answers by processing the data.
Thirdly, the massive volume of data that is collected, collated, and organized has to be dealt with the right software to analyze it. The scale, volume, variety, and the velocity of the data generated have to be handled by the chosen software to ensure they give the right results with the influx of the anticipated data streams. This is even truer as most of these data streams will be unstructured and raw in nature, it needs to be pre-processed and transformed with the tools like the Pig component of Hadoop and then stored in the database. Suitable Analytics tools should also be deployed which can analyze spontaneous streams of real-time data that IoT would generate. The analytics solution that the businesses structure should also be according to the business strategy and plans keeping in account the velocity, variety and the volume of data IoT would generate.
- Eventually, we are advancing towards a more connected world where more intelligent and interconnected devices would exchange data to provide services that would improve the quality of our lives.
- Furthermore, when the product data is combined with other data like commodity prices, inventory metrics, and locations, service histories, etc., the value of it increases exponentially helping businesses to build newer business models and innovate newer products based on real-time data.
- The volume, velocity, and variety of data will exponentially increase calling for better data infrastructure, data centers, cloud-based computing, and data clusters.
- The analytics solution that the businesses structure should also be according to the business strategy and plans keeping in account the velocity, variety and the volume of data IoT would generate.