The evolution of the internet has been one of the most important events of the 20th century. It has opened up a whole new world of interconnectivity and communication. The internet was a revolution that has impacted almost every single aspect of our lives. However, if you think that there are no other things in the pipeline that can match the power and impact of the internet, you may well be in for a surprise. The internet may have changed your life, but the Internet of Things (IoT) is set to change it all over again. IoT here implies machines embedded with sensors or iBeacons that collect and store data for analysis. The insane amount of data generated by IoT will call for increasing use of Data Analytics to process this massive amount of data.
Data science and IoT
We are pretty well aware of the fact that Data Science is a multidisciplinary field that relates to the processing of mammoth amounts of data (both structured and unstructured) so that they can be stored and analysed to derive valuable insights and meaningful information from them. However, the important question here is whether data generated by IoT and data generated by other sources are one and the same or are they different.
As a data scientist, you are expected to be fluent in various concepts of Matrix Algebra, Optimization techniques, Bayesian statistics and implementation of supervised and unsupervised algorithms. You need to be fluent in all the above mentioned maths concept of data science if you are dealing with data generated by IoT. And when it comes to programming, IoT datasets require knowledge of programming languages like Python and R as well.
Challenges associated with the Implementation of Data Science for IoT
Building data products and running analytics applications with IoT is complex and not as easy it initially seems. Organizations have to contend with a lot of challenges like performance limits, dynamic modeling, data types and volume changes and last but certainly not the least, the cost associated with hiring competent data scientists. Security is also a major issue as the stupendous growth of IoT devices brings into serious question the ability to maintain the privacy of users. Additionally, IoT devices generate massive amount of data every second and organizations have to find innovative ways to log this data in order to extract valuable insights from them.
The development of processes for transforming data into useful insights is a crucial part of succeeding at IoT and big data. If you too are struggling to know the impact of IoT on Big Data and Data Science, then you should join Internet of Things Training Program
through a premier institution. This will equip you with the desired knowledge and skills to use the data at your disposal to draw actionable insights and take helpful business decisions, which is necessary for the long-term success of your organization and to protect it from any losses.