Technology & Engineering

2812/2016

The Missing Link in Why You’re Not Getting Value From Your Data Science

By |December 28th, 2016|Categories: Internet Of Things (IoT), Predictive Analytics, Predictive Maintenance, Technology & Engineering|Tags: , , , , , , |

The Missing Link in Why You’re Not Getting Value From Your Data Science

by Robert Morris, Ph.D.

DECEMBER 28, 2016

Recently, Kalyan Veeramachaneni of MIT published an insightful monologue in the Harvard Business Review entitled “Why You’re Not Getting Value from Your Data Science.” The author argued that businesses struggle to see value from machine learning/data science solutions because most machine learning experts tend not to build and design models around business value. Rather, machine learning models are built […]

2107/2016

What did the Coffee Pot say to the Toaster?

By |July 21st, 2016|Categories: Internet Of Things (IoT), Technology & Engineering|

The Internet of Things (IoT) is at the precipice of the Gartner Hype cycle and there is no shortage of the “answers to everything” being promised. Many executives are just now beginning to find their feet after the storm wave that was the transition from on-premise to cloud solutions and are now being faced with an even faster paced paradigm shift. The transformative tidal wave that is IoT is crashing through CEO, CTO, and CIO’s […]

1301/2016

What makes a successful UI for a startup?

By |January 13th, 2016|Categories: Technology & Engineering, Uncategorized|

No one really knows… until they have some real customers and real users.

Friends reach out for help when joining a new early stage startup, or looking for ideas on what it would take to build a UI for a startup they are thinking about starting.  This is some of the info I give them, so I figured this might help others to.  Is this “best practices”, or “industry standards”? No, but might lead you to the […]

1510/2015

How Predikto hired thousands of data scientists

By |October 15th, 2015|Categories: Predictive Analytics, Technology & Engineering|Tags: , , , |

GE’s Jeff Immelt was recently interviewed on the Predictive Analytics investments and overall initiatives that have been ongoing over the last 5 years within his walls. The transcript, available here, is an excellent read on how a legacy company is attempting to transform itself for the digital future, leveraging vast amounts of sensor data to predict failure in large machinery. This marks a pivotal moment in GE’s history, where turning around a Titanic-size ship won’t […]

1004/2015

Using the Spark Datasource API to access a Database

By |April 10th, 2015|Categories: Predictive Analytics, Technology & Engineering|Tags: , , , , |

At Predikto, we’re big fans of in-memory distributed processing for large datasets. Much of our processing occurs inside of Spark (speed + scale), and now with the recently released Datasource API with JDBC connectivity, integrating with any datasource got a lot easier. The Spark documentation covers the basics of the API and Dataframes. There is a lack of information on actually getting this feature to work on the internet, however.
TL;DR; Scroll to the bottom for the complete Gist.
In this […]

1108/2014

Forget the Big Data technology chat and ask “How will I use this?”

By |August 11th, 2014|Categories: Predictive Analytics, Technology & Engineering|

The Industrial Internet of Things is going to revolutionize the way enterprises interact with their assets and equipment. Bill Ruh, VP of Global Software Center at GE, says GE expects there will be 17 Billion unique pieces of equipment by 2015 and only 10% of the devices are equipped with sensors today. Most of the equipment with sensors lacks the basic intelligence they hope to have in the future which is to tell them when […]

1006/2014

Here comes the flood-analytics, Manufacturing Industries!

By |June 10th, 2014|Categories: Manufacturing, Predictive Analytics, Predictive Maintenance, Technology & Engineering|

Yes – we have heard about the magic of predictive analytics and how it has helped various companies and industries in predicting the rise and fall of companies’ finances, social media and marketing and such but could the same predictive analytics methods aid manufacturing industries today?

According to Bala Deshpande’s article, manufacturing industries are not entirely oblivious to the idea of collecting data. As a matter of fact, you could call them ‘The Forefathers of Data […]

2401/2014

M2M Analytics Will Generate $14 Billion by 2018

By |January 24th, 2014|Categories: Predictive Analytics, Predictive Maintenance, Technology & Engineering|Tags: , , |

Senior analyst, Aapo Markkanen, from ABI Research forecasts that the M2M analytics and big data industry will grow 53.1% over the next 5 years from US $1.9 billion in 2013 to US $14.3 billion in 2018.

The forecast includes revenue segmentation for the five components that together enable analytics to be used in M2M services:
1) Data integration
2) Data storage
3) Core analytics
4) Data presentation
5) Associated professional services

Predikto is uniquely positioned to make an impact in this transformational […]

2001/2014

Experts should let Algorithms do the talking

By |January 20th, 2014|Categories: Predictive Analytics, Technology & Engineering|

Andrew McAfee wrote an interesting blog post on HBR titled” “Big Data’s Biggest Challenge? Convincing People NOT to Trust Their Judgment”. I have picked a few of the main points below, but the entire post is worth a read. McAfee concludes that we should turn many of our decisions, predictions, diagnoses, and judgments—both the trivial and the consequential—over to the algorithms. When presented with this evidence, a contemporary expert’s typical response is something like “I […]