05 Apr

How Internet of Things impacts Data Science and Analytics

How Internet of Things impacts Data Science and Analytics

Internet of Things is fast becoming a reality with more and more entities being connected to the internet in the grand scheme of things. This will have a profound impact on the way we interact with one another and the manner in which businesses are run. Gartner predicts that revenue from IoT products and services will touch $300 billion by 2020. But the same report affirms that this is just the tip of the iceberg.

The kind of data that will be generated will be overwhelming to say the least. But it is always good to know how IoT can impact the way we deal with data science and the possibilities of using analytical tools on an altogether different level to unearth hitherto unheard insights and information.

So here’s a look at how Internet Of Things can be a real game changer:

The repercussions of IoT will be felt far and wide and it is good to take stock of the situation so that enterprises can get themselves ready by deploying the right strategies and processes in place. Companies will have to upgrade their tools and apparatuses and also stay on top of emerging technologies in order to fully benefit from the opportunities thrown up by IoT.

Internet of Things Technology

Storing data on an unprecedented level

All that deluge of big data means big storage requirements and thus most companies would not be able to handle such kind of data capabilities in-house. There is a need to outsource data handling process using platform as a service or infrastructure as a service. All this ensures that data generated by IoT can be conveniently stored in data centers that are highly reliable, scalable, economical, flexible and compliant with the various architectural and hardware nuances.

When storing data on the cloud there are multiple options of private, public and hybrid cloud options. If the data falls under one of sensitivity and the need for compliance with regulatory issues, you can store it in the private cloud. Otherwise a public or a hybrid cloud option would be a good option.

IoT Around The World

Deploying big data technologies

Handling big data comes with its own set of threats and opportunities. Thus there is a need for using the right technology. Data agility is a hot topic of discussion and the larger the data, the bigger the issue of data agility. So using IoT can pave the way for using data on an unprecedented level and this poses new challenges for improving data agility.

Big data comes with the attributes of 4 Vs which stand for velocity, variety, veracity and volume. So with the rise of big data it is necessary that all personnel handling the data should have knowledge of data storing, migration, upgrade, integration, checking for authenticity, analysis and use of right strategy to derive business intelligence out of it.

Securing the data at scale

Since IoT consists of various devices connected to the internet there are a lot of ways in which data can be compromised and fall in the wrong hands. So this calls for security measures to ensure that data security is top priority.

Data can be compromised while in transit or at the place of storage. Thus different checks and balances have to be put in place in order to see to it that data is secure. Multiple levels of encryption and security have to be followed in order to safeguard the data from unscrupulous elements.

Protecting the privacy

In order to ensure that brands and individuals do not suffer privacy concerns there is a need to take steps to ensure that privacy of the data is respected at all times. This should not be confused with data security since privacy is a different issue. The people who legitimately handle the data should ensure that privacy is not breached at any time.

A lot of insights can be derived from all that data that is stored and collected. But the owner of the data should be crystal clear at all times. This makes sure that it does not fall in the wrong hands and privacy concerns are respected and remain paramount throughout the life cycle of the data.

Customer Satisfaction

Analytics and data governance

With a big deluge of data comes big insights but only if the data is analyzed properly. So there is a need for analytical software at a scale that can take in raw data and convert it into nuggets of information. Also, data governance becomes a prime task in order to ensure the right data is available at the right time to the right person. Managing the data involves maintaining, cleaning, storing, protecting, segregating, consolidating, upgrading and integrating it in order to derive benefits from it.

Analytical tools will be available on demand and in the cloud so that companies do not have to go for upfront investment. So depending on the field of concern and the data that needs to be analyzed it is possible to hire such services in order to gain useful insights. A lot of free analytical tools are also available that can be used by organizations for gaining competitive advantage.

Key Takeaway: Internet of Things is upon us and with it comes big opportunities for brands that are at the forefront of exploring newer opportunities. It is about always being on your toes in order to find out what is the next trending thing in this field so that it can be deployed at scale in order to take advantage of IoT. No wonder IoT will pose new challenges to enterprises in unprecedented ways but it shall also open new doors for conducting business at an altogether different level.