Thomas Henson

  • Data Engineering Courses
    • Installing and Configuring Splunk
    • Implementing Neural Networks with TFLearn
    • Hortonworks Getting Started
    • Analyzing Machine Data with Splunk
    • Pig Latin Getting Started Course
    • HDFS Getting Started Course
    • Enterprise Skills in Hortonworks Data Platform
  • Pig Eval Series
  • About
  • Big Data Big Questions

Where Were You When Artificial Intelligence Transformed the Enterprise?

June 10, 2019 by Thomas Henson Leave a Comment

Blog Post First Appeared on Dell EMC Post “Where Were you When Artificial Intelligence Transformed the Enterprise“…

Where were you when artificial intelligence (AI) came online? Remember that science fiction movie where AI takes over in a near dystopian future? The plot revolves around where a crazy scientist accidentally put AI online only to realize the mistake too late. Soon the machines become the human’s overlords. While these science fiction scenarios are entertaining they really just stoke fear and add to the confusion about AI. What enterprises should be worried about regarding AI, is understanding how their competition is embracing it to get a leg up.

Where were you when your competition put Artificial Intelligence online?

Artificial Intelligence Transformed the Enterprise

Artificial Intelligence in the Enterprise

Implementations of artificial intelligence with Natural Language Processing is changing the way enterprises interact with customers and conduct customer calls. Organizations are also embracing another form artificial intelligence called computer vision that is changing the way Doctors read MRIs and the transportation industry. It’s clear that artificial intelligence and deep learning are making an impact in the enterprise. If you are feeling behind no problem let’s walk three strategies enterprises are embracing for implementing AI in their organizations.

Key Strategies for Enterprise AI

The first key point to embracing AI into your organization is to define an AI strategy. Jack Welch said it best “In reality strategy is actually very straightforward. You pick a general direction and implement like hell.”  Designing a strategy starts with understanding the business value that AI will bring into the enterprise. For example, a hospital might have an AI initiative to reduce the time to recognize from CT scans patients experiencing a stroke. Reducing that time by minutes or hours could help get critical care to patients and bring out about better patient outcomes. By narrowing and defining a strategy Data Scientist and Data Engineers now have a goal to focus on achieving.

Once you have a strategy in mind, the most important factor in the success of artificial intelligence projects is the data. Successful AI models cannot be built without it. Data is an organizations number one competitive advantage. In fact, AI and deep learning love big data. An artificial intelligence model that helps detect Parkinson’s disease must be trained with considerable amounts of data. If data is the most critical factor, then architecting proper data pipelines is paramount. Enterprise must embrace scaled out architectures that break down data silos and provide flexibility to expand based on the performance needs of the workload. Only with scale-out architectures can Data Engineers help unlock the potential in data.

After ensuring data pipelines are architected with a scale-out solution, it is time to fail quickly. YES! Data Scientist and Data Engineers have permission to fail but in a smart fashion. Successful Data Science teams embracing AI have learned how to fail quickly. Leveraging GPU processing allows Data Scientist to build AI models faster than anytime in human history. To speed up the development process though failures, solutions should incorporate GPUs or accelerated compute. Not every model end with success but leads Data Scientist closer to the solution. Ever watched a small child when they are first learning how to walk? Learning to walk is a natural practice of trial and error. If the child waits until she has all the information and the perfect environment they may never learn to walk. However, that child doesn’t learn to walk on a balance beam it starts in a controlled environment where she can fail. A Data Science team’s start in AI should take the same approach, where they embrace trial and error while capturing data from failures and successes to iterate into the next cycle quickly.

Want More Data Engineering Tips?

Sign up for my newsletter to be sure and never miss a post or YouTube Episode of Big Data Big Question where I answer questions from the community about Data Engineering questions.

Filed Under: Business Tagged With: AI, Business, Enterprise

GDPR Good or Bad?

June 7, 2018 by Thomas Henson Leave a Comment

GDPR Good Or Bad

Is GDPR Good or Bad?

How many emails have you received about GDPR? At this point I almost have to set a rule in Outlook to send all emails with the word “GDPR” in them to a separate folder. I’ve explained what GDPR is and how it applies to Data Engineer but is it good or bad. Generally regulations are put in place to make society better, but does Big Data need regulation? Find out my thoughts on the policies put in place with GDPR in the video below.

Transcript – GDPR Good Or Bad?

Hi folks! Thomas Henson here, with thomashenson.com. Today is another episode of Big Data Big Questions. Today, I’m going to jump back in a little bit more around GDPR. We want to find out, had a lot of questions, seen a lot of things on Twitter, and I just thought it would be a great time to discuss, is GDRP [Phonetic] good or bad?

This is not going to be about politics. It’s going to be about policy and what’s really driving GDPR. What does it really mean, as far as, is that a good thing for us that are involved in big data? And, it’s consumers. Find out more, right after this.

[Sound effects]

Welcome back. This is the second episode where we’re going to talk about GDPR. If you’re curious about what GDPR is and what it means to data engineers, make sure you check out the video that I did before just talking about, what does GDPR mean to data engineers, machine learning engineers, or data scientists?

I really wanted to focus this time on, we’ve talked about what it is, but what does it really mean? Is it a good thing? I’ve gotten a ton of emails just on my personal stuff, from people who’ve built websites for me, from different HortonWorks, and Cloudera, and everybody’s kind of talking about, what does GDPR mean to us? Every time you turn around right now, you’re going to have to update some kind of policy, whether it be from Apple on your iPhone, or from Android, or anybody that’s collecting or holding onto your data, all those privacy updates are all going on, and you’re going to have to click yes on each one of them.

Yes, I understand that you’re going to protect my data, and it’s going to be more private. Is that a good thing or is it a bad thing? Is it okay for us to have regulation around it?

I look at it from this perspective. I was thinking about it, and it’s like, if you really think about where we’re going, there’s regulation for everything. For most products, as they get big. What this really means to me, and why I think it’s a good thing, is because this shows that your digital data is growing up. It’s maturing. When you think about it, in America, when cars first came out, we didn’t really have regulations around it. You didn’t have to get a license. It was just something fun that you could do, and if you could afford a car, you could get it. As that product started maturing, we started realizing, “Hey, this is something that needs to be regulated to some extent.”

We need to have some kind of standards around who’s going to drive on what side of the road, and how all that’s going to work through. If you think about digital data, we’re getting to that point. A couple reasons why we’re at that point, if you think about it, the first thing, privacy matters. Privacy’s always kind of mattered, and people really pay attention to being able to be private and have those things. For a long time, data has not seen one of them.

We have regulations and laws around if people can go into private residencies without consent and things like that. Your data, it’s the same way, and that’s where we’re starting to look at it and say, “Okay, that data, you have rights to it. It’s yours. You created it, so your privacy does matter.” That’s where the regulations are coming. Also a big thing is, think about how many different data breaches we have.

For a long time, if you follow Troy Hunt, or anybody that’s big in security, you can always see at least weekly, they’re talking about a huge data breach that happened. That compounded with trying to figure out, “Okay, if you’re collecting these data, how much of a liability, how much is that for you, and then how much of a responsibility is it of yours if the data becomes breached? Are there certain standards that you should have to follow to be able to better protect that data, so that you can turn around and say, “Hey, we do have some bad actors out there, that have hacked and taken this data, but we went through these steps.”

There’s not really been a standard for what those steps are, and so this is a further implementation of it. The thing, and one of the reasons, a couple of the reasons, actually, that I think that it’s a good thing, right? Not talking politics here, just why I think GDPR’s good.

It gives you back control of your data. It gives you the opportunity to say, “Hey, I would like for you to be able to report and see what data you have on me. What does my digital footprint look like?” What kind of data are you collecting on me? You have the authorization to ask for that and to be able to get an answer to that.

Secondly, you can say, “Hey, I want to drop off. I want all my data gone. I don’t want you to collect and hold onto my data.” I think this is a big point, because while I’m on Facebook, and I’ve been a Facebook user for I don’t know how long, just a long time, I’ve heard of other people and other stories around people who’ve gone off Facebook. You’ve probably not seen them. They’ve deleted their profile, only to come back a year or two later, and all their stuff’s still there.

I can’t say that I’ve seen that happen for me, but I’ve heard a ton of stories, where I know that there much be some sort of truth to that. This is an opportunity where, if you do want to get off the grid, so it’s like, “Hey, you know, it’s 2018, I’m going to get off the grid,” this gives you the opportunity. That’s another reason why I think it’s really good. It puts you in control of your data and lets you decide.

Also, it’s going to create a framework for companies to have a standard around how they’re going to protect that data. It’s going to protect companies and organizations that collect data by having a set of standards that we’re able to follow, to say, “Hey, we’re doing as much as we can to be able to protect, and make sure that, your data, when it comes in, is as secure as can be.” This gives us the opportunity to start setting those standards and testing it. Maybe we won’t have as many data breaches in the future.

Maybe, we can trust and understand that, while there are bad actors out there, that maybe there will be less involvement around the hackers, because it really puts the onus on the people who collect the data. We had some of that before, but a lot of it has been, I would say, public perception. You want your public perception to be okay. How much of a law, and really bearing, is going to be on companies if that data is discovered, or data is breached? Now, this gives us the framework to say, “Hey, there are regulations, and we are saying that, you know, this is something that you need to protect.”

That was just my thoughts on it. I’d love to hear your thoughts. If anybody has any opposing views or anything like that, put them in the comments section here below or just reach out and ask. Let’s jump on YouTube, and let’s record a video, and maybe talk about it a little bit more. Let me know where I’m wrong, but, that’s my thoughts. I think, in general, GDPR is good. I think there’s going to be a lot of opportunities around products and around people with that expertise, so if you’re looking to get involved in big data, and you like looking into and following regulations, and putting security metrics into works, then I think GDPR is a good place to go.

I think there’s going to be a lot of companies that are going to make products. There’s going to be products that are out there, that’s going to help with GDPR compliance, because May 25th’s coming, 2018. I don’t know that everybody’s going to be ready. Until next time.

Filed Under: Business Tagged With: GDPR

Degree with Experience

February 2, 2012 by Thomas Henson Leave a Comment

e-commerce book

A few months ago I read this post from Dave Yankowiak that was asking the question if usable experience is more valuable than a college degree. With college tuition going up and the average student 20K plus in debt, his analysis might be spot on.

Gaining experience is necessary for landing that first opportunity post graduation. But that experience can come while pursuing your degree. A lot of times students can find internships or co-ops through their college career center. That experience can help students network and sharpen there skills.

For my personal experience I was able to take my current job in a restaurant, and begin doing small IT related tasks. These tasks at first where done as extra tasks Pro-Bono. The more projects I accomplished the more trust I gained to take on more complicated projects. After graduation I was able to use that experience I gained to start off as a level II developer versus level I.

The most important thing to make the most of your time in college and try to get experience wherever you can.

This is a sample of the skills I learned in college:

  1. Java
  2. VB.Net
  3. PHP
  4. SQL
  5. Oracle
  6. HTML
  7. CSS
  8. AJAX
  9. Access
  10. MYSQL

For me, learning these skills was important in landing my first job after graduation.

Filed Under: Business, Development

Site Relaunch

December 7, 2011 by Thomas Henson Leave a Comment

Alot has been going on since my last post in September. I have been working on setting up a babies room (this will be our first child), also I have been busy working with the site relaunch. While updating the website I looked at other blogging frameworks/ platforms but have stayed with WordPress. The WordPress community has so much support it is hard to match.

Here are a few changes to the Blog:

  • Changing Themes
  • Adding Twitter feed
  • Incorporating Video Blogs

Future:

  • Some technical reviews
  • Video tutorials

Thanks for your support.

 

Filed Under: Business, Development

Adding New Content

September 19, 2011 by Thomas Henson Leave a Comment

Brand New Sign

 

Weeks have passed since I have set up my Web Application and it feels like nothing is getting accomplished. Here are a few items I need to address:

Develop New Theme

  • Roadblock: Seems to be the configuration of my XAMP and IIS not working together properly. (Really they do not work together because they both want to use port 80). Solution is to have one use a different Port!!!

Add Contact Page

  • Roadblock: The Idea behind the page has been drawn up but I have yet to code the page just yet. Look forward to a release next month.

New Images

  • Roadblock: Fireworks vs Gimp or better yet Open Source vs Propriety. Images are very important part of any web design, but as a small business budgets are equally important. Another consideration for is time, Fireworks is something I am comfortable with while GIMP is an unknown application. A post will be released breaking down both of the applications.

Check back next week to see the progress and see more tips of how to create your own Development Company.

*Developing a new small business requires constant portfolio management. This Web Application was created to help developers in their small business development.

Filed Under: Business

Subscribe to Newsletter

Archives

  • February 2021 (2)
  • January 2021 (5)
  • May 2020 (1)
  • January 2020 (1)
  • November 2019 (1)
  • October 2019 (9)
  • July 2019 (7)
  • June 2019 (8)
  • May 2019 (4)
  • April 2019 (1)
  • February 2019 (1)
  • January 2019 (2)
  • September 2018 (1)
  • August 2018 (1)
  • July 2018 (3)
  • June 2018 (6)
  • May 2018 (5)
  • April 2018 (2)
  • March 2018 (1)
  • February 2018 (4)
  • January 2018 (6)
  • December 2017 (5)
  • November 2017 (5)
  • October 2017 (3)
  • September 2017 (6)
  • August 2017 (2)
  • July 2017 (6)
  • June 2017 (5)
  • May 2017 (6)
  • April 2017 (1)
  • March 2017 (2)
  • February 2017 (1)
  • January 2017 (1)
  • December 2016 (6)
  • November 2016 (6)
  • October 2016 (1)
  • September 2016 (1)
  • August 2016 (1)
  • July 2016 (1)
  • June 2016 (2)
  • March 2016 (1)
  • February 2016 (1)
  • January 2016 (1)
  • December 2015 (1)
  • November 2015 (1)
  • September 2015 (1)
  • August 2015 (1)
  • July 2015 (2)
  • June 2015 (1)
  • May 2015 (4)
  • April 2015 (2)
  • March 2015 (1)
  • February 2015 (5)
  • January 2015 (7)
  • December 2014 (3)
  • November 2014 (4)
  • October 2014 (1)
  • May 2014 (1)
  • March 2014 (3)
  • February 2014 (3)
  • January 2014 (1)
  • September 2013 (3)
  • October 2012 (1)
  • August 2012 (2)
  • May 2012 (1)
  • April 2012 (1)
  • February 2012 (2)
  • December 2011 (1)
  • September 2011 (2)

Tags

Agile AI Apache Pig Apache Pig Latin Apache Pig Tutorial ASP.NET AWS Big Data Big Data Big Questions Book Review Books Data Analytics Data Engineer Data Engineers Data Science Deep Learning DynamoDB Hadoop Hadoop Distributed File System Hadoop Pig HBase HDFS IoT Isilon Isilon Quick Tips Learn Hadoop Machine Learning Machine Learning Engineer Management Motivation MVC NoSQL OneFS Pig Latin Pluralsight Project Management Python Quick Tip quick tips Scrum Splunk Streaming Analytics Tensorflow Tutorial Unstructured Data

Follow me on Twitter

My Tweets

Recent Posts

  • Tips & Tricks for Studying Machine Learning Projects
  • Getting Started as Big Data Product Marketing Manager
  • What is a Chief Data Officer?
  • What is an Industrial IoT Engineer with Derek Morgan
  • Ultimate List of Tensorflow Resources for Machine Learning Engineers

Copyright © 2023 · eleven40 Pro Theme on Genesis Framework · WordPress · Log in

 

Loading Comments...