Chapter 13. Bringing It All Together

The President of Operations at your company, previously the VP of Connected Services and your boss, smiles as he firmly shakes your hand.

"Revenues are up 10% and it is clearly attributable to the work of your team," he says. "The CEO and I have decided to create a new position, Vice President of Connected Analytics. I want you to lead it."

"Thank you and I hope to earn the confidence placed in me," you say, trying to hide your smile.

"Oh, you already have that," he winks, "You can tell your team. They stay with you and we're adding a data management team and a frontend prototyping team to your group. Did I tell you that we are doubling the number of IoT products in the next fiscal year?"

He nods and turns to stroll away still smiling.

"You start immediately," he says over his shoulder.

You think to yourself,

I finally made it. After all the work and stress, I made it

. You enjoy the thought for a few minutes. Until you come to the realization:

Wait, how am...

Review

The range of steps in the flow of IoT data from the device to the presentation of analytic results was covered in this book. This is a wide range of topics, but it does all fit together. The following diagram maps this out and shows how each chapter in the book relates:

General IoT data and analytic flow as covered in this book.

The IoT data flow

In order to understand a complex system, such as the flow of data from IoT devices, or the flow of risk and money in a Collateralized Debt Obligation (CDO), as depicted by the IMF in the following diagram, you need to map out the process. Then, you need to understand how each stop along the way contributes to the end result. This can help avoid unprofitable projects - and worldwide recessions.

How AAA assets were created out of subprime mortgages - money flow diagram. Source: IMF

 

We discussed the many challenges with IoT data. It is notoriously messy, and will often have missing and incorrect values. In Chapter 1, Defining IoT Analytics and...

A sample project

If you are ready to challenge yourself, the following is a project that you can work out how to do on your own. There is no education like actually doing the work yourself, especially when you are not sure of the right answers:

The project steps are as follows:

1. Set up the AWS environment: Follow Chapter 4,Creating an AWS Cloud Analytics Environment to prepare a secure area for data storage and IoT analytics.
2. Build a data feed to NOAA hourly weather data: You could use Python code in an AWS Lambda function or a service such as Amazon Kinesis to process the feed.
3. Import the dataset into a Hadoop environment (store in HDFS): Practice querying data using Hive. Amazon EMR can be used for this or a Cloudera/Hortonworks distribution.
4. Combine with another data set: You choose; have fun.
5. Analyze with Tableau to understand the data: Connect to Hive and explore the combined data. Create a dashboard to communicate some metrics and alerts.
6. Use R to create a machine learning prediction model...

Summary

This chapter reviewed the main themes of this book. We also added some short, boiled-down advice. Finally, we presented a challenge project - have fun with with it.

Good luck and happy hunting for IoT value through analytics!