Article | April 2, 2020
The outbreak of coronavirus has taken many countries under its hood. Most of them are suffering from economic loss and a higher mortality rate. Amid this, governments are in a great dilemma how to handle the circumstances around the falling economy and upsurging coronavirus infections. In order to get better hold onto situations across their countries, they are moving towards innovative technology adoption. Out of all the new-age technologies, big data and data analytics can serve with a great opportunity, where governments across various nations can understand the outbreak analytics.
Article | February 20, 2020
The world is now heading into the Fourth Industrial Revolution, as Professor Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, described it in 2016. Artificial Intelligence (AI) is a key driver in this revolution and with it, machine learning is critical. But critical to the whole process is the need to process a tremendous amount of data which in turns boosts the demand for computing power exponentially.A study by OpenAI suggested that the computing power required for AI training surged by more than 300,000 times between 2012 and 2018. This represents a doubling of computing power every three months and two weeks; a number that is significantly quicker than Moore’s Law which has traditionally measured the time it takes to double computing power. Conventional methodology is no longer enough for such significant leaps, and we desperately need a different computing architecture to stay ahead in the game.
Article | February 12, 2020
The upsurge in data generation and its computing has raised the need for more power, storage and speed. What we call as big data is extremely memory-hungry and power-sapping and to fetch this requirement, engineers have put forward an innovative method. Recently, electrical engineers at Northwestern University and the University of Messina in Italy have developed a new magnetic memory device that could potentially support the surge of data-centric computing, which requires ever-increasing power, storage, and speed. Based on antiferromagnetic (AFM) materials, the device is the smallest of its kind ever demonstrated and operates with record-low electrical current to write data.
Article | January 21, 2021
The Internet of Things has been the hype in the past few years. It is set to play an important role in industries. Not only businesses but also consumers attempt to follow developments that come with the connected devices. Smart meters, sensors, and manufacturing equipment all can remodel the working system of companies.
Based on the Statista reports, the IoT market value of 248 billion US dollars in 2020 is expected to reach a worth of 1.6 Trillion USD by 2025. The global market is in the support of IoT development and its power to bring economic growth. But, the success of IoT without the integration of data analytics is impossible. This major growth component of IoT is the blend of IoT and Big Data - together known as IoT Data Analytics.
Understanding IoT Data Analytics
IoT Data Analytics is the analysis of large volumes of data that has been gathered from connected devices. As IoT devices generate a lot of data even in the shortest period, it becomes complex to analyze the enormous data volumes. Besides, the IoT data is quite similar to big data but has a major difference in their size and number of sources. To overcome the difficulty in IoT data integration, IoT data analytics is the best solution. With this combination, the process of data analysis becomes cost-effective, easier, and rapid.
Why Data Analytics and IoT Will Be Indispensable?
Data analytics is an important part of the success of IoT investments or applications. IoT along with Data analytics will allow businesses to make efficient use of datasets. How?
Let’s get into it!
Using data analytics in IoT investments businesses will become able to gain insight into customer behavior. It will lead to the crafting offers and services accordingly. As a result, companies will see a hike in their profits and revenue.
The vast amount of data sets that are being used by IoT applications needs to be organized and analyzed to obtain patterns. It can easily be achieved by using IoT analytics software.
In an era full of IoT devices and applications, the competition has also increased. You can gain a competitive advantage by hire developers that can help with the IoT analytics implementations. It will assist businesses in providing better services and stand out from the competition.
Now the next question arises: Where is it being implemented? Companies like Amazon, Microsoft, Siemens, VMware, and Huawei are using IoT data analytics for product usage analysis, sensor data analysis, camera data analysis, improved equipment maintenance, and optimizing operations.
The Rise of IoT Data Analytics
With the help of IoT Data Analytics, companies are ready to achieve more information that can be used to improve their overall performance and revenue. Although it has not reached every corner of the market yet, it is still being used for making the workplace more efficient and safe.
The ability to analyze and predict data in real-time is definitely a game-changer for companies that need all of their equipment to work efficiently all the time. It is continuously growing to provide insights that were never possible before.