Get fresh updates from Hortonworks by email

Once a month, receive latest insights, trends, analytics information and knowledge of Big Data.


Sign up for the Developers Newsletter

Once a month, receive latest insights, trends, analytics information and knowledge of Big Data.


Get Started


Ready to Get Started?

Download sandbox

How can we help you?

* I understand I can unsubscribe at any time. I also acknowledge the additional information found in Hortonworks Privacy Policy.
closeClose button

Deriving Analytic Insights from Machine Data and IoT sensors

Recorded on November 3rd, 2016

Hadoop and The Internet of Things has enabled data driven companies to leverage new data sources and apply new analytical techniques in creative ways that provide competitive advantage. Beyond clickstream data, companies are finding transformational insights stemming from machine data and telemetry that are radically improving operational efficiencies and yielding new actionable customer insights.

During this webinar we will:

  • Discuss real world case studies from the field across a variety of verticals
  • Describe the strategies, architectures, and results achieved by Fortune 500 organisations
  • Outline the best practices on how to improve your operational efficiency


Sunil Godse says:

Looking forward to participate

Rizwan says:


Barbu says:

Hi! You mentioned that 80% of the analytics work flow consists in data cleaning, feature engineering, dimensionality reduction etc. before building the predictive model itself.
One of the commonly used tools in the engineering for this purpose is Matlab.
Was this tool part of the ecosystem?
Thank you!

John says:

Hi Barbu, Thanks for your question. We don’t typically see MatLab used in the data cleansing process. It’s generally a combination of Hadoop and ETL tools transforming and cleansing data either as part of the loading process or once it has landed within the platform. John

bairuitao says:

Great. That’s what we need.

Comments are closed.

In association with :