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Smart Data Discovery - The next wave in BI



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Smart Data Discovery – the Next Wave in Business Intelligence

In our always-on, ever in demand world, technology moves at a breakneck speed for both consumers and business. Keeping up with the trends can be mindboggling and 2017 is no different. Last year we touched on the top three emerging trends in the insight and analytics sector. From increased data security scrutiny to healthcare data to smart data for the masses; it’s been nearly a year since we wrote about these emerging big data trends. So, let’s take a deeper dive and see where we are, what’s changed, and what to watch.

One of the most quickly evolving trends is smart data discovery according to Gartner’s 2017 BI and Analytics Magic Quadrant. As the Digital Age progresses, this next wave of business intelligence automates analytics through machine learning and natural language. Businesses will need people who can understand, manage, and guide the process as projections show smart data discovery to be mainstream within three years.

Finding the Balance

Most companies need to balance between a structured setup and a need for data discovery. Finding the balance can help guide them to informed decisions about investing in their analytics capabilities. Consistent data definitions may be best in a more centralized approach, while more complex issues may be solved by a combination of smart data employees utilizing machine learning tools for analysis.

It’s important to recognize not everyone in the organization has the time, talent, or interest involved in data discovery. But, they still need the information gained from analysis beyond a standard report format.

FUN is in the Fundamentals

As exciting as combining machine learning process with new data discoveries is, it’s key not to forget the foundation of prep work. Technology needs those who understand what data is important to a business and how it should be managed.

Data discovery is key to every business and isn’t just related to customer insight and marketing in consumer industries, it’s important in the financial services sector as well. This is where our team of experts comes in. If you’re interested in contributing to the future of big data, we might have the role for you. We specialize in Data and Analytics recruitment and always have a wide range of vacancies at both junior and senior level. Take a look at our current vacancies or contact us to find out more.

For the East Coast and Mid-West teams please call 212-796-6070, or email newyorkinfo@harnham.com.

For the West Coast team call 415-614-4999 or email sanfraninfo@harnham.com.

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Computer Vision in Healthcare Beyond Covid-19

2020. It sounds like the name of a futuristic science-fiction movie or TV show, doesn’t it? Maybe it is. And like our favorite sci-fi flicks there are cutting edge changes happening in real time. We’re the characters in this story and the Computer Vision and Artificial Intelligence partnerships in healthcare are moving fast to help us take care of ourselves. When computers can see what we can’t. When AI can help us make more informed decisions. When the two are combined to help doctors and providers work more efficiently to save lives, that’s when the cutting-edge shines. From the collaboration of Johns Hopkins, the CDC, and the WHO mapping out the data to contact traces to medical professionals on the front lines, we’ve been focused on one thing. Saving lives. But, what about the other medical issues that affect us? Heart disease. Cancer. Neurological illnesses.  What if the latest advances in healthcare could help here, too? Five Ways Computer Vision Helps Healthcare Providers Identifies leading causes of medical illnesses in a time-sensitive manner by creating algorithms for image processing, classification, segmentation, and object detection.Develops deep learning models to create neural networks.Collaboration of teams of scientists working together for the advancement of projects and present findings to business leaders, stakeholders, and clients.Allows providers to spend more time with their patients.Optimization of medical diagnoses using deep learning so doctors can spend more time with patients to help see and solve the problem faster. Computer Vision Engineer Meets AI Professional Artificial Intelligence (AI) offers real world answers in healthcare the world needs today. Computer Vision Engineers build the means to which AI helps providers, patients, and leaders make informed decisions. Core requirements for both roles include, but aren’t limited to: Experience in machine learning and deep learning.How to build computer vision algorithms and probability models.Problem-solving skills, creativity, ingenuity, and innovation.Languages like Python, R, Hadoop, Java, and Spark.Be able to see the big picture while at the same time finding the devil in the details. Always striving to improve, to make better, to advance the technology within the industry. The Challenges and the Potential of Technology in Healthcare At the moment, Computer Vision, AI, and other healthcare technology models are localized to individual placements. The next step is to have these technologies ‘speak’ to each other across hospitals, provider’s offices, telehealth applications, and electronic health records management for a more cohesive benefit of care. As this year rounds to a close, we know the vulnerabilities of our healthcare system, and can find solace in the though that technology is bringing it forward at lightning speed. Automation and telehealth appointments have made it a breeze to talk to our doctors and get results faster. We can pay our bills with the click of a button and even carve out a payment plan, if need be. All without leaving our homes. The data now available to us and our providers offers a foundation, a benchmark of information, so our doctors can make more informed decisions. This data goes beyond the individual, it helps set a precedent for not only individuals, but also entire populations, to help us identify future health issues, epidemics, and pandemics.  Stored data is private and stays within its construct of hospital or doctor’s office, but from it we can create models to plan for the future. Want to make your make your mark in the healthcare and tech industry? We may have just the role for you. Check out our current vacancies or get in touch with one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Jenni Kavanagh

Jenni Kavanagh

15. October 2020

A Slam-Dunk Career as a SLAM Engineer

Philadelphia. It’s known for it’s Philly Cheesesteak, the Liberty Bell, and where the Constitution was signed. Always on the cutting edge, Philadelphia is a land of firsts. You may or not know this, but one of its firsts was to have the first general use computer in 1946. Is it any wonder then that a company there is building robots to navigate GPS denied environments and was begun by leaders in the Computer Vision space?  Beyond the Roomba If you consider the Roomba, the autonomous vacuum that sweeps up pet hair, dirt, and other unwanted product, how does it know where to go? How does it know to go under a table or chair or around a wall to the next room? How does it know to avoid the dog, cat, or you? On nearly the smallest scale, this little round machine is a personal version of simultaneous location and mapping (SLAM).  However, the computational geometry method of this mapping and localization technique extends in a wide variety of arcs. Here are a few to get you thinking: GPS Navigation SystemsSelf-driving carsUnmanned Aerial Vehicles (UAV)Autonomous Underwater Vehicles (AUV)DronesRobotsVirtual Reality (VR)Augmented Reality (AR)Monocular Camera...and more There’s even a version which is used in the Life Sciences called RatSLAM. But we’ll visit that in another article. The uses and benefits of this simultaneous location and mapping technique are exponential even with some of the challenges posed by Audio-Visual and Acoustic SLAM. What is SLAM? Essentially, it is the 21st century version of cartography or mapping. Except in this case, not only can it map the environment, but it can also locate your place in it. When you want to know where the nearest restaurant is, you simply type in ‘restaurant near me.’ And soon, a list appears on your phone with a list radiating from nearest location outward.  Imagine you’re lost on a hike, you manage to find signal, and soon your GPS is offering directions on which way to move toward civilization.  This is Simultaneous Localization and Mapping. It locates you, your vehicle, a robot, drone, unmanned aerial vehicle or self-driving car and puts people and things in the direction it thinks they want to go or should go to get to safety. While mapping is at the epicenter of SLAM Computer Vision Engineering, there are other elements within the field as well. But let’s begin with mapping. Topological maps offer a more precise representation of your environment and can therefore help ensure consistency on a global scale.  Just as humans do when giving directions, sensor models offer landmark-based approaches to make it easier to determine your location within the map’s structure and raw-data approaches which makes no assumptions. Landmarks such as wifi or radio beacons are some of the easiest to locate, but may not always be correct which is where the raw-data approach comes in to offer its two cents as a model of location function. Four Challenges of SLAM GPS sensors may not function properly in chaotic environments such as military conflict. }Non-static environments such as pedestrians or high traffic areas with multiple vehicles make locations difficult to pinpoint.In Acoustic SLAM, challenges include inactivity and environmental noise as well as echo. Sound localization requires a robot or machine to be equipped with a microphone in order to go in the requested direction. Five Additional Forms of SLAM Tactile (sensing by touch)RadarAcousticAudio-Visual (a function of Human-Robot interaction)Wifi (sensing strength of nearby access points) Ready to Explore a Robotics and Computer Vision Career? Whether you’re interested in a slam dunk career as a SLAM Engineer or looking for your first or next role in Big Data, Web Analytics, Advanced Analytics & Insight, Life Science Analytics, or Data Science, take a look at our current vacancies or get in touch one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.

Mairead Holt

Mairead Holt

08. October 2020

How Machine Learning and AI Can Help Us See the Forest for the Trees

In the early days of 2020, Johns Hopkins, the CDC, the WHO, and a host of other public organizations banded together in collaboration. They were on a mission to ensure the world had real-time information to a virus that would forever chance the course of this year and the years to come. Which is great for those families with a computer in every home or every person with smartphone access. But what about the rest of the world? How do you ensure those people without access to basic needs lives can be improved? A health non-profit using AI and Machine Learning is aiming to do just this. But the Data is vast and the sheer numbers of people need to be corralled by someone into something the computers can read and make decisions on. Who would have thought Public Research and Data Science would come together in such a manner and in such an important time? Three Benefits of Data Science and Machine Learning in Healthcare According to a seminar given in September 2019, two research scientists explained to the CDC the promises and challenges using Big Data for public health initiatives. After explaining a few definitions and making correlations, the focus was soon on the benefits. The focus of Machine Learning is to learn data patterns.From the initial focus, patterns can then be validated to ensure they make sense.These patterns and validation of patterns can find links between seemingly uncorrelated factors such as the relationship between one’s environment and their genetics. To the scientists working with these scenarios, the decisions seem simple. Yet, when it comes to explaining them to laymen like policymakers, there can be a shift in understanding. This shift can lead to arbitrary and different findings which can affect medical decision making. Why? Could it be using Random Forests in linking the data could be confusing?  Data Classification is Not as Cut-and-Dried as a Work Flow or Org Chart If someone shows us a work flow or organizational chart, we understand immediately each task to be done in which order or who reports to whom. But in trying to link uncorrelated bits of information using decision trees, it can seem more like abstract art, more subjective than direct. Yet, it is those correlations which answer the bigger questions brought to bear by Research Scientists, Public Health Researchers, the Data Scientists, and AI working together to see the bigger picture. Decision trees, ultimately, are the great classifier. But there are a few things which need to be in place first. Yet, in the random forest model it’s not just one decision tree, it’s many. This is definitely a case where, if you done right, you will see the forest for the trees and at the same time be able to determine patterns in those trees. A bit counter-intuitive, but this is what stretches our minds to see correlations and patterns we might not see otherwise, don’t you think? So, what do you need to help make predictions?  Two Important Needs to Help Make Predictions Predictive power. The features you employ should make some sense. For example, without a basic knowledge of cooking, you can’t just throw random items from your refrigerator into a pot and expect it taste good. Unless of course, you’re making soup and all you have to do is add water.The trees and their predictions should be uncorrelated. If you’ve ever seen M. Night Shymalan’s Lady in the Water, there’s a little boy who can ‘read’ cereal boxes and tell a coherent story. A predictive coherent story. This is the layman’s version of random forests, their predictive nature, and ultimately, the scientists who can ‘read’ and explain the patterns. If you're looking for your first or next role in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Tim Jonas

Tim Jonas

01. October 2020

Leading Remote Teams in the Land of Beer, Barbeque, and Tech

Charlotte, North Carolina known for its beer and barbeque is not the first location to jump to mind when you think digital hub. But here’s the rub, it is. In the Fall of 2019, the city and Microsoft signed a three-year digital alliance. And as the country moved from office locations to work-from-home and remote operations, Charlotte became a prime destination for tech.  Four Skills for Leading in the New Normal Whether you’ve learned to balance work time with virtual schooling or have been working from home for years, there are some skillsets which set leaders apart. The first one may surprise you. Let others lead – According to our most recent salary guide, one of the main reasons people leave their jobs is due to poor management. With the rise of remote working, hierarchy has flattened to a degree as everyone must discipline themselves. Micromanagement becomes almost moot as everyone leans into this learning curve. Lead by example and let others take over the leadership driver’s seat from time-to-time. Balance both Soft and Technical Skills – While technical skills are the backbone of subject matter experience in a Digital Analytics role, it’s the soft skills which can help set you apart. Sure, you’ll want to know the ins and outs of web analytics and optimization, but you’ll also need to have the skills to explain findings and offer recommendations to address client needs. Know When to Pivot – Life throws us curveballs. Consider 2020, for example. Whether you must pivot for survival or simply need to take things in a new direction, knowing when to pivot and how to explain it to your employees is a leadership skill inherent for this new normal. Be Approachable – With open door policies moved online, leaders will want to determine the best way to recreate opportunities for employees that need to talk outside the daily or weekly staff meeting. Having insight into how your team works best, can help you guide them toward success. Programs to know and experience to have often include the technical knowledge you’ll need to ensure your client makes the most informed decisions.  ‘Smart Cities’ of the Future At the beginning of 2020, as the coronavirus came to call, someone joked that in 2020 we’d hoped to have flying cars and smart cities of the future, but instead were being taught how to wash our hands. Perhaps they weren’t far off on the smart cities quip as both Houston, Texas and Charlotte, North Carolina are on the cutting edge of creating these smart cities. Things like Massive Open Online Courses (MOOCs), LinkedIn Learning, even the Entrepreneur Store offers classes and bundles in everything from computer language learning such as C++, R, and Python to Digital Marketing and Graphic Design. But, learning these things and more on a Microsoft campus can catapult students into more jobs and helps guide cities in smart power grids, smart busses, autonomous cars, and the list goes on. Experience in a design agency who works within both the B2C and the B2B verticals helps to expand opportunities exponentially. Remote working opportunities have opened up worlds of collaboration, teamwork, and focus on the next steps into the future. Whether you’re interested in a remote working leadership role in the beachy Carolinas or looking for your first or next role in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Joe Gibbs

Joe Gibbs

10. September 2020

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