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Big data was seen as one of the biggest buzzwords of 2013, when companies often used the term inappropriately and in the wrong context. This year, people will finally understand what it means
One could look back at 2013 and consider it the breakthrough year for big data, not in terms of innovation but rather in awareness. The increasing interest in big data meant it received more mainstream attention than ever before. Indeed, the likes of Google, IBM, Facebook and Twitter all acquired companies in the big data space. Documents leaked by Edward Snowden also revealed that intelligence agencies have been collecting big data in the form of metadata and, amongst other things, information from social media profiles for a decade.
And beyond all of that, big data became everyone's most hated buzzword in 2013 after it was inappropriately used everywhere, from boardrooms to conferences. This has led to countless analysts, journalists and readers calling for people to stop talking about big data. A good example could be seen in the Wall Street Journal last week, where a reader wrote in complaining:
A lot of companies talk about it but not many know what it is.
While that's a problem, it leads to my first prediction:
1. In 2014, people will finally start to understand the term big data. Because, as it stands, many do not.
The truth is that we've only really just started to talk about big data and companies aren't going to stop screaming about their latest big data endeavors. In fact, it's only January and the social bookmarking network Pinterest has already acquired image recognition platform VisualGraph. (Why? Pinterest want to understand what users are "pinning" and create better algorithms to help users better connect with their interests).
So let's get 2014 off on the right foot with a definition of big data, from researchers at St Andrews, that's fairly easy to understand:
The storage and analysis of large and/or complex data sets using a series of techniques including, but not limited to: NoSQL, MapReduce and machine learning.
The main elements revolve about volume, velocity and variety. And the word 'big'? If your personal laptop can handle the data on an Excel spreadsheet, it's not big.
Matt Asay, a journalist with ReadWriteWeb, also does a good job in explaining what makes a big data problem (as opposed to more traditional business intelligence).
If you know what questions to ask of your transactional cash register data, which fits nicely into a relational database, you probably don't have a big data problem. If you're storing this same data and also an array of weather, social and other data to try to find trends that might impact sales, you probably do.
2. Consumers will begin to (voluntarily) give up certain elements of privacy for personalization.
We've all heard of cookies – and we know that our actions around the internet affect the adverts that we see on websites and the suggested items we receive on Amazon. This is a concept that we've not only become accustomed to but also accept. After all, if we're going to have information put in front of us, we'd rather that we could relate to it.
But there have been problems in the past. Some websites have taken advantage of customers, for example increasing the prices for a flight that they've previously expressed interest in (consumers might worry that the price will go up even further and therefore decide to buy a ticket).
But as more companies instil big data techniques, customers will cooperate, on the premise that they will benefit. This is likely to follow Tesco's methodology, whereby customers are sent vouchers for goods that they are likely to buy anyway, creating a win-win situation for both parties. Customers, generally, are happy to receive a discount and retailers are pleased customers are coming back (especially if vouchers have an expiry date).
3. Big data-as-a-service will become a big deal
Despite claims from analysts that all businesses will look to hire data scientists, this just isn't going to happen. Firstly, there's a shortfall of data scientists, which goes some way in explaining why companies are retraining existing staff to work with big data) and secondly, not all companies are ready to (nor do they need to) invest in full-time data scientists to analyze and explain their data.
Instead, just as in other areas, I expect a wave of companies hustling to enter the big data-as-a-service space, an idea that began to creep into the latter parts of 2013. This could be anything from small and medium businesses signing up to anything from entire packages of storing, analyzing, explaining and visualizing data to more compact services, which focus on transferring data to cloud-based servers to allow for an accessible way of questioning the data in the future.
4. And finally... remember how Hadoop is an open-source software? Expect a lot more of that.
Hadoop, famously named after a toy elephant, is a well known piece of software to anyone curious about data science and it provides the backbone for many big data systems, allowing businesses to store and analyze masses of data. Most importantly, it's open source, which means that its implementation was inexpensive, allowing many organizations to understand, rather than ignore, the data they were collecting.
Quentin Gallivan, the chief executive of business analytics software firm Pentaho, explained last month that the rise of new open-source software will bring about more innovation and more ways of understand the data. He said:
New open source projects like Hadoop 2.0 and YARN, as the next generation Hadoop resource manager, will make the Hadoop infrastructure more interactive... projects like STORM, a streaming communications protocol, will enable more real-time, on-demand blending of information in the big data ecosystem.
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With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.
Visit our News & Blogs portal or check out our recent posts below.
Black Friday, once reserved for the Friday after Thanksgiving, has a new lease on life. It’s not just one day a year. Now, it can be any day of the year. Why? Customers the world over appreciate the deals and discounts as they get ready for the holidays, and the insights gleaned from previous years help businesses determine what will sell best in the current year. Add in the rise of mobile marketing in which you can buy anything, anywhere, anytime, and more people working from home than ever before, and you have the recipe for Black Friday every day. Especially once the leaves begin to Fall and the holiday season comes knocking at our doors. Behind Advanced Analytics & Insights within the Data profession, there are a host of professions which together help to create the products and launch them. Who could imagine the science behind the sales? Five Important Roles Behind Advanced Analytics & Insights There’s a reason that Data professionals are no longer siloed and must work across and within departments. Data influences every decision within business today. So, having the right people on your team in the right roles can ensure your business thrives. Marketing Analyst Using a spoke-and-wheel analogy, the Marketing Analyst is the spoke. These are the professionals central to taking the information from their Campaign Analysts, Pricing Analysts, and Statistical Modelling experts to determine what will sell best and what price. In essence, their research and Data helps companies figure out ‘what the market will bear.’ Campaign Analyst Focused campaigns to a target market will find a Campaign Analyst understands consumer behaviors. Once the customer is understood – what they buy, when they buy, why and how they buy – can help analysts measure, review, and justify each campaign to justify ROI.Consumer Insights While the Campaign Analyst is focused on targeted campaigns to specific customers, the Consumer Insights Analyst helps businesses tailor their marketing strategies to meet the needs of those customers. All of them. Whether they’re part of a targeted marketing campaign or if they’re prospective clients ‘window shopping’ when they download a ‘free product or click on an email’. Understanding these consumers helps to convert from passing interest to the purchase of a product or service. Statistical Modelling Analyst Do you love puzzles? A jumble of pieces which need to be put together so everyone can see the full picture? Statistical Modelling are the jigsaw puzzle solvers of the Marketing department. These professionals pull together data from multiple sources and analyze the information to help form a clear picture of their ideal consumer. Toss in a bit of psychology – why customers do what they do and predict what they might do next – and your executives will understand the best way to distribute funds to grow their business. Pricing Analyst It seems simple enough. Determine how much it cost to produce a product or service and mark it up to make a profit, right? Not exactly. These days, calculating not only what it cost to make a product, any overhead to consider, and how much you need to mark it to make a profit is a complex prospect. Factor in what your competition is doing…on a global scale. Consider the fickle buying power of consumers – some days money flows and some days it’s reigned in tight. How do you determine the best price at the right time to ensure maximum profit while keeping pulse on spending patterns? Pricing Analysts take complex data, study customer spending habits, and conduct analyses on what the math says and what the impact might be. So, back to Black Friday sales. Taking what we know of the roles which help businesses set the tone for their marketing strategies, Black Friday every day makes sense. We’re home more. The lines between work and family life are blurred, but computers and phones are at our fingertips, and everyone delivers what we need right to our door. Why not get a jump on your holiday shopping? And once that’s done, you can focus on what your plans are for the future. Are you looking for a career change or just want to see what the market looks like within the Data professionals industry? There is plenty of information to be collected and analyzed. What role might you fill? If you’re looking for a role in Data & Analytics or are interested in Advanced Analytics & Insights, Harnham may have a role for you. Check out our current vacancies or contact one of our expert consultants to learn more. For our West Coast Team, contact us at (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
12. November 2020
COVID-19 may have rocked the world of employment, but it also created a whole new series of opportunities. If you are looking for work, there are a few updates to the rules of the job search. Not rules, really. More preferred guidelines. A Note on the Guidelines of the Job Search Remember when your work experience was honed to two pieces of paper – your resume and cover letter – and you hoped it made it to the hiring manager? Well, there are a lot more direct ways to get there and plenty of opportunities abound to help you stand out from the crowd. It’s not just your educational experience. In fact, today’s hiring is much more about emotional intelligence, collaboration, and how you use what you’ve learned in previous roles. Among the negative notes, there are a host of positive movements for jobseekers with both established and startup firms. And sometimes, even within a legacy firm which has pivoted with the changes of our new world of work. Thread the Needle of Responsibility Google and IBM may be leading the charge to hire without use of a degree, but most businesses still want that piece of paper. How you present it is another matter. Think video, project portfolios, and online forms via application tracking systems (ATS). That’s just to get you in the door. The more important hurdle is understanding the nuances of your role and responsibilities. The list of qualifications and duties has always been part of the job search. Do you fit all the requirements? Can you handle all the responsibilities? Did you read between the lines to understand what the company hopes will find in their ideal candidate to help them meet their business goals and objectives? Below are some questions you might ask yourself when reading through job descriptions or considering where you’d like to apply: Are you able to not only craft reports, but also see patterns to help you gain insight into what the reports are telling you?From this, can you not only discuss it with your colleagues and teammates, but also across departments, executives, and stakeholders?Can you not only explain the patterns to both technical and non-technical audiences, but do so across multiple projects?What challenges will you face and how will you solve them?How well do you manage your time? Can you step in to lead a team or do you prefer to work on your own? Could you be flexible between the two?Are you able to build relationships both internally and externally – teammates, vendors, executive leaders, department heads, and the board room.Do you have emotional intelligence? Can you take ownership of a project and hold yourself and others accountable?Do you show initiative? Not just in diving into a project, but asking questions. Can you ask objective questions playing devil’s advocate on one side and seeing the possibilities on the other? These are wide open questions to challenge yourself. Some are leadership-centric. Some are simply ‘can I do the job?’ questions. But, ultimately, it’s these kinds of questions which are asked in interview under the purview of seemingly inane questions. They’re meant to make you think and for the hiring manager to see how you think. 3 Surprising Ways to Stand Out in Your Job Search With the rise of remote working, Zoom, and Slack, the video interview and application process has gained ground. It’s quickly become the virtual way to seek, apply for, meet with, hire, and work with prospective and current team members. But, if you’re in the tech space, you can go even deeper than video and you’ve got more than project portfolios to fall back on. Write about your experiences – what you’ve learned, where, why, and how. Think Medium’s Toward Data Science. Don’t forget to hit publish! Not a writer? Follow the blog and make comments.Network – this seems like a ‘no brainer’, but in our somewhat virtual world it can be even easier for those who already comfortable in this environment. Whether it’s via LinkedIn or Twitch, you are building relationships to help you move forward in your job search.Use your skills to help you run and track your job search more efficiently. If you’re interested in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our expert consultants to learn more. For our West Coast Team, contact us at (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
29. October 2020
What do you get when you combine Amelia Earhart with Ada Lovelace? A Data Visualization Engineer ready to work with an aviation industry partner. Reaching new heights and shattering the glass ceiling is the modus operandi for many women, and what better role models than the ladies listed. Creative, free-spirited, pioneering, and well before their time in thoughts and action. Ada Lovelace, now attributed as the first computer programmer saw beyond the automatons of her day. She saw beyond the Berullean language in front of her she was translating. A poet father and a passion for numbers collided into her thoughts and as we marvel at AI making art, writing stories and music, and winning strategy games, we have one lady to thank. Ada. She might also be called the first Data Visualization Engineer. Don’t you think? Insightful Business Decisions are Key in Collaboration Data professionals are no longer siloed from other departments in business allowing for collaboration between teams. In partnership between both technical and non-technical employees, businesses can be sure they’re teams have a single vision to help realize business objectives and goals. The collaboration between Ada Lovelace and Charles Babbage may not have been business-related, but the ideas are the same. He passed her the document and asked her to translate, she made notes, and those notes have made history. Together they created a vision for The Analytical Machine – it exists only on paper, but it’s design, layout, and potential implementation are realized in ways unimaginable to most 100 years ago.Ada’s mathematical prowess was such that she wrote her notes in easily explainable language.She worked closely with Charles Babbage and wrote in earnest to work with Michael Farraday – she reached out to others in her field, some accepted, others didn’t. How Data Helps Inform the Future Whether you use predictive modeling, machine learning, natural language processing, or some combination of each, the data you collect helps to inform the future. We may often lament the old adage that those who don’t know their history are doomed to repeat it, but history has a shining light as well. Collaboration across the ages. Consider this. Alan Turing, the man who worked in Bletchley Park with the Enigma machine, used the notes he found to help him solve the problem. Those notes belonged to Ada Lovelace. The information she set to paper informed every stage of computer programming leading to what we know today as Artificial Intelligence. Machines that could learn and ‘think,’ not just the automatons of her age which had been ‘programmed to perform.’ The Enchantress of Numbers Known as the Enchantress of Numbers, the pioneering Ada Lovelace shares the spotlight with other pioneering women in the sciences. Think Madame Curie, Joan Clarke, even Hedy Lamarr, and of course Amelia Earhart. They weren’t of the same eras, but each of their contributions have added to what we know as the Science, Technology, Engineering, and Mathematics (STEM). We have a name for it now, but it’s always been around. And the collaborative efforts of women everywhere are growing and increasing diversity and inclusion in many businesses across the world. And at the heart of it all, in the beginning, a surprising and time-defying collaboration began. It set in motion a spark of business intelligence and insight as men and women mentored and partnered for the sake of their vision of the future. Who will be remembered one hundred years from now? If you’re interested 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 firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
22. October 2020
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 firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
15. October 2020