Webinar: Smart analytics to address big data challenges

About Webinar

Data is the most valuable resource for businesses, which contains extremely valuable information about business processes as well as many other important aspects. Since a massive volume of both structured and unstructured data is being generated every second, organizations may fail to use this data to its full potential. As a result, they cannot gain insights required to take smart decisions.

In our webinar, we will explain what smart analytics is and how it can help businesses tackle the challenges of big data and generate actionable insights for effective decision-making. With the help of data scientists and data visualizers, you can build big data and smart analytics solutions that will unlock significant opportunities lying in your company’s existing data.

Webinar agenda

• The evolution of data
• Overview: What is smart analytics?
• Smart analytics vs. traditional reporting tools
• Why do businesses need smart analytics today
• How can it help you take smart decisions?
• Smart analytics tools and technologies
• Smart analytics in action
• How to get started
• Q&A

Questions & Answers

The following are the answers to the questions that were asked during the live webinar.

Question 1: How do I go about implementing a smart analytics solution in my manufacturing unit? What are the prerequisites for initial setup?

Answer 1: To perform smart analytics and generate futuristic insights, all you need is data. Data can be generated from sensors or your historical data- both can help you generate new insights and take smarter decisions. You need to find out the opportunities to generate possible, new insights as well as existing problems that can be resolved with critical analysis of data.

Question 2: Is it possible to plan an effective maintenance program without having any sensors in place?

Answer 2: Yes, definitely. Effective and predictive maintenance is not dependent on sensors data, rather on historical data and service logs.

Question 3: Does smart analytics include a machine learning element within it?

Answer 3: Yes. Smart Analytics has an important element called Data Science. Plus, Machine Learning is part of Data Science so it can be part of smart analytics that we would perform. However, it all depends on the nature of analytics that we are looking for.

Question 4: Can you explain how and where the data is stored?

Answer 4: To perform smart analytics, it hardly matters where and how the data is stored. Smart analytics can exchange data irrespective of where it resides. However, if you are looking for real time insights then we must have the cloud server set up in order to process the streaming data.

Question 5: Is it required to hire full time data scientists for setting up smart analytics solutions?

Answer 5: It depends on the scalability, complexity and your business requirements. But, ideally you should start with a smaller and quicker smart analytics solution and then determine further.

Question 6: Do smart analytics solutions require any kind of human interaction once set up?

Answer 6: There are a few smart analytics use cases that can be fully automated depending upon technical feasibility available within the system. In other words, YES- smart analytics brings many opportunities to make your system fully automated.

Question 7: How much difficult it is for our staff to analyze and visualize data provided by sensors?

Answer 7: Reports and dashboards produced as an outcome of the smart analytics are intuitive and self-explanatory. Instead of poring over spreadsheets or reports, visualizing large amounts of complex data in form of chart and graphs is easier.

Question 8: How can I build a big data and smart analytics solution that helps in making smart decisions?

Answer 8: You can start with our IoT kick start program. This workshop will help you to understand why and how you should initiate your Internet of Things project with a concrete proof of concept for your business.