Data Security - From your staff to the cloud



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Data Security - From Your Staff to the Cloud

With news of hacks, leaks, and intergovernmental interference, you may want to consider how best to secure your own company’s data. Whether you run a call center or a credit and finance institution, sensitive data is transmitted and held in physical storage devices and in cloud storage. Cloud storage is increasingly popular to file sensitive information. But, some experts warn of mistakes companies make in securing data. Specifically in regard to cloud storage, some experts suggest a need to add security layers to data stored in the cloud.

Rather than simply file away data in storage files similar to paper files in cabinets, companies must consider and create policies to track how and with whom files are shared. With policies and procedures in place, content controls, tracking processes, and deep analytics, security and workflow holes can be more easily secured. But, as important as policies and procedures are, it’s important to educate staff on the importance of data security.

Staff is First Line of Defense in Datacenter Security

Begin with the devices. As remote working continues to evolve, consider the devices which leave the office building in staff’s hands and make sure those devices are secure. Set rules and regulations in regard to data privacy outside the office. No matter your role on the IT team, manage up. Educate staff on the importance of data security and make sure they understand they’re the first line of defense.

Consider what controls are in place to ensure proper handling of sensitive data. Where is your data located and who has access? Make sure to encrypt it whether it’s being transmitted across networks or simply in storage. Educate staff and layer your security measures to ensure data is kept secure.

Be aware of user endpoints. Where is the data going and who has access as it is these endpoints which are often least protected. Consider your end user and put policies in place to guard against unencrypted or non-password protected files. Endpoints such as mobiles, tablets, and laptops are particularly vulnerable.

Setting Standards to Mitigate Risk

When it comes to data security, most businesses use a one-size fits all approach. But, their strategic objectives, risk, and value of data used to assess security risk are varied. In considering datacenter security, many organizations consider the implications of big data and its applications. From real-time fraud detection to smart power grids to complex competitive analysis, big data is characterized by three main factors: volume (how much data is transmitted daily), velocity (the speed at which data is transmitted), and variety (the range of data transmitted).

As you think through the security implications of your datacenter and the best strategies for implementation, keep in mind the following. Educating users and staff is important to a solid data security strategy. Be sure to not only have policies and procedures in place, but also update them regularly.

Securing your datacenter is paramount to an effective and efficient organization. Having the right team in place can ensure peace of mind. 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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Junior Data Scientists Set To Scale Up In 2019

We’re at a unique time in our history, in which there are more jobs available than people to fill them. Major employers are looking at apprenticeships, free degrees, or simply abandoning degree requirements altogether. There is one field, however, which affords candidates a range of industries, apprenticeship opportunities, and advancement like no other field before. Data. Much like the freshman congress just entering the House of Representatives, Junior Data Scientists are at a distinct advantage as we enter 2019. If you’re a Junior Data Scientist interested in advancing your skills and seeing where it can take you. This is your year.  Careful at the Curve Like many changes which seem to happen both too quickly and not quickly enough, there will be a learning curve in 2019 and in the years to come. It will be felt by everyone; business and data professional alike, but it’s important to realize that like all growing pains in regard to change, things will get better.  The talent shortage, particularly in the US, as of August 2018 was estimated to be 151,217. Places like New York City, Los Angeles, and San Francisco felt the brunt of this shortage. This skills shortage affects everyone and could strain a company’s ability to deliver, unless there is a strong scaling strategy in place.  It’s at this crossroads, the prevalence of Junior Data Scientists can help bridge the strain. However, too much too fast could also lead to potential misinterpretation of data causing some to fall short on their ROI. Part of learning is making mistakes and being aware there is a learning curve as Senior and Junior Data & Analytics professionals work together toward the company’s common goal. According to LinkedIn’s Workforce Report for January, hiring has been moderate with a 4.1% increase over that of December 2017. In the continuing pulse of the Fourth Industrial Revolution, tech skills still reign. Soft skills, though, are increasingly in demand as everyone levels up to keep up in regard to business management skills, strategy, and digital transformation across enterprise endeavors. So, what are some ways to maximize your opportunities. Below is a quick overview: Skills for the New Year, New You Tech Skills  Artificial Intelligence, Machine Learning, and Data Visualization are a few of the top skills needed in the new year. Language processing skills and knowing which tools are best for which problem e.g. Python, SQL, R, Excel and Scala. Data storage, optimization, and modeling can help lay formulate strategy by knowing where data is, the best data to use, and what it can do to create information for actionable insights aligned with business practices. Quantitative and Predictive Analysis, and Software Development are additional building blocks for skills-based knowledge for any data professional. Business Management Skills Strategy, vendor management, change management. Not only are tech skills important, but as the business landscape itself changes and c-suite executives level up their own data and digital transformation skills, it’s important for Data Scientists to do the same. They should understand the business sector they’re working in so they can create solutions to complex problems which align with their company’s objectives, goals, and logistics. Communication Skills  It can be all too easy to get caught up in the minutiae of detail and work singly on a project, but it is here communication becomes key as it helps bring in other departments to help analyze the data correctly. These departments may include those in a non-technical field such as marketing, and the data professional must be able to clearly and fluently translate their findings.  Evaluate how your goals and skills align. Find others who have a similar mindset, but be open to new opportunities. You never know what skills you might inherit when you branch out of your comfort zone. Create Your Own Curriculum for Lifelong Learning Opportunities Practice deliberately, build your own project, give and get feedback on your work, and track your progress.  The Future So Far… In general, the Data Science job outlook continues skyward as vast amounts of data requires skilled professionals to clean it, and determine how and why it’s going to be used. Someone must be able to unravel this information to not only increase its value, but be able to explain what they’ve learned in plain language to non-technical professionals, business executives, and in many cases board and/or stakeholders. If you’re interested in Big Data & Analytics, we may have a role for you. We specialize in Junior and Senior roles. Check out our current vacancies or contact one of our recruitment consultants to learn more.  For our West Coast Team, call (415) 614 4999 or send an email to sanfraninfo@harnham.com. For our Mid-West and East Coast Teams, call (212) 796 6070 or send an email to newyorkinfo@harnham.com.

How Cities Are Using Big Data

High speed trains in Florida. Driverless cars in Arizona. National grid union agreements. All these and more are working to create a more smoothly operating system of infrastructure. While privacy laws and transparency vie for attention at every level of government in the US, cities have taken the onus of using data to make decisions.   The functionality a critical infrastructure society is built on – railroad tracks, flare stacks, power lines – has been brought together by robotics and AI. The decentralization of intelligence, cloud systems which remotely control Industrial IoT, and AI are just a few of the ways in which 2019 will be a breakout year for Distributed AI. New York City Uses Data to Alleviate Damage Risk to Buildings In their race to stay ahead of Big Data, they may also find ways to improve they might never have discovered without it. New York City has limited staff who can analyze its million properties and incorporate analytics to discern fire risk considering past risk and building traits. City coding has therefore become more important than ever to alleviate potential risk.   Philadelphia Focuses on City Interaction with its Residents Evidence-based decision making has debuted in Philadelphia’s GovLabPHL, a multi-agency collaboration. Together, they are centralizing and digitizing records making information easier to share among agencies that historically kept information to themselves. With everything in one place, they can provide city services to their residents much more effectively and efficiently. Florida’s First High Speed TGV Train Rolled out late last year, this high-speed train travels from Miami to West Palm Beach with plans to branch into Orlando and Tampa soon. America’s first high speed passenger train in years will help alleviate road traffic, noise pollution, and more. Data collected may include best safety measures, business practices, and economic value to the city and its residents as money shifts from car buying to rail ticket purchases. The Ethics of Data and Potential Risk of Bias Gaining insights into human behaviors, ease of transportation, and predictive information to curb damage to buildings and other city properties are all important to a smart city’s infrastructure. But, data is, after all, input by humans and isn’t infallible; falling prey to natural biases. Researches and analysts caution decision-making from computer-based algorithms isn’t perfect and should be considered with discretion. For example, the rise in AI, face recognition software, traffic cams, and statistics currently on file may hold a prejudice against certain ethnicities based upon their developer’s biases. This is especially glaring in criminal behavior predictions and as such, policymakers need to think critically and to not take technology at face value. After all, those inputting the data are human, and our biases have a way of seeping into our information. In 2019, AI systems are no longer the robotic machines once shown in movies as something to fear. Today, vendors who build these systems must not only focus on the value provided, but also consider moral foundation of their service. It’s important to understand exactly why and how data will be collected and with whom it will be shared. As cities and businesses continue to catch up, this knowledge is necessary for long-term viability, credibility, and transparency. Trust is a crucial element of data strategy.  See Through Cities – Transparency is Key City governments and researchers are working to lessen discriminatory outcomes by turning to transparency. Major cities such as Philadelphia and New York have opened up their websites and invited the public to examine information and their methods of interpreting the data. New York implemented a task force to study how the city uses data and its goal is to present in December of this year ways the city should assess its automated decision-making for transparency, equity, and opportunity. This is a pivotal year for cities to understand their urban ecosystems. Understanding challenges such as traffic, pollution, parking and inefficiency of movement in urban areas may help realize how, when, and where people are moving. With core infrastructures in place, movement may be reduced. In addition, mobility will become efficient and lessen people’s need to move around for better jobs and/or housing. AI is the tool to help cities gain visibility into this type of data. It will enable not only visibility, but also foster prediction capabilities, and provide actionable insights to improve our understanding of why, how, and the way we move. If you’re interested in Big Data & Analytics, we may have a role for you. We specialize in junior and senior roles. Check out our current vacancies or contact one of our recruitment consultants to learn more.  For our West Coast Team, call (415) 614 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast Teams, call (212) 796 6070 or send an email to newyorkinfo@harnham.com.

I, Human – Navigating Data with Analytics and AI

Big Data tomes sit on a number of business reference shelves. Machine Learning, Analytics, and Edge Computing books compete for space in our minds, on our computers, in the cloud, and on the shelf. Over the past year, we’ve talked about the Data Scientist shortage, what Web Analytics mean to businesses, how AI will work hand-in-hand with humans and, if you’re looking for a career, how to stand out from the crowd. As the year comes to a close and we look to the new year, we wonder what 2019’s trends will be. What will change exponentially? What and who is lagging and leading? And how to navigate the soon to be third stage of ubiquitous data. Data is everywhere and, in some instances, can be too much to wade through. So, in a world of juxtapositions, the next wave of trends is to make Big Data small which will ultimately utilize AI more efficiently. Biting Off More than We Can Chew Much like the idea of music in your pocket with the introduction of the iPod, the latest trend in Big Data is to make it small, bite-sized, and navigable. So, how do you make Big Data small? The tsunami of data we encounter on a daily basis is staggering and overwhelming. As data teams become unsiloed, so too, does data. As vendors, digital leaders, business executives, and data professionals come together into a centralized team, data is being streamlined into a single view within a hub. Open source sharing, collaborating, and use of enterprise data catalogs within the hub add more value to businesses and can help to drive data management strategy.  But, though education, training, and apprentice-like experiences, even the best data professionals can have trouble navigating the swathes of data they encounter each day. Enter AI. These systems are intended to cut through the data, filter the information based on algorithms it’s given and, when needed, “learn” what it needs to know to process information, and accurately share what it has discovered. From there, humans can take the information and analyze how it can be of benefit to the business and what actionable insights can, and should, be implemented. I, Human One of the more nefarious predictions of the past few years has been the fear that robots and AI would take over jobs. But, just as the dishwasher and laundry machine were developed to ease time at those chores, AI is the answer to how to increase productivity, not take over.  Though AI has the capability to handle a range of tasks, it cannot replace hands-on, human-centric tasks. In retail, for example, AI might be used to make the process of shopping and buying more streamlined while freeing up the salesclerk to offer more focused customer service. A restauranteur could create the perfect ambience setting based on data about noise level, food preferences, busy vs slow times, and in so doing develop a customer base with whom they could discuss where the food comes from, offer classes, and more. AI is intended as a partnership to humans. Assisted productivity to free up time for more creative and complex pursuits. Beyond the industry executive, 2019 is predicted to be the year AI enables IT to move past routine automation tasks and proactively streamlines processes. With the assistance of AI, people will be able to work smarter, not harder, be more effective, and more productive. If you’re interested in Big Data & Analytics, we may have a role for you. We specialize in junior and senior roles. Check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, call (415) 614 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast Teams, call (212) 796 6070 or send an email to newyorkinfo@harnham.com.

2020 Vision for the Future of Work

Timing is everything. Market research, consumer trends, and digital transformation. They all share the structure of right time, right place for the product, service or, in this case, digital trend, and directly impact how work gets done. Change on a massive scale once took centuries to complete. Today, change happens in real-time and reshapes businesses in months, not years. Jurassic Changes in the Digital Age To stay in the market and ahead of competitors, it’s important for leaders to embrace digital and all it entails. Even within the digital transformation of work, there will be three periods of growth, in which some businesses have blossomed and others have failed. Disruption is a given. Hyper-digital is now. Universal transformation is just around the corner. Disruption – add the word “tech” to any industry and even the industry name embraces the technology to create value and improve customer service growing response times to minutes, not hours or days. Demand for instant assistance grew. Hyper-digital –What was once a luxury or novelty quickly became a household or business “can’t do without it” device or service. Digital technology adoption accelerated at lightning speed. Universal Transformation - The convenience of all-in-one will be widely adopted and required. As we look to year 2020, we’re firmly in the hyper-digital age. Understanding technologies, we have now such as Big Data and analytics, and how to utilize their information for business is critical for making plans. This information can help prioritize budgets, schedule implementations, and even plan out investments into what and when to maximize returns. However, this will require strategic planning, and a roadmap to guide and time technology application and implementation for businesses. It will be important for leaders to know why. Why they need this particular technology at this specific time, and how it will help them move forward in their business goals. Delegating Data Mobile and digital consumers have reached unprecedented levels. Departments from marketing, sales, IT, and data teams race to keep up with the demand for instant information. Hyper-vigilance in today’s hyper-digital world requires humans to upgrade their abilities, and learn how to delegate data to the technologies available such as AI and analytics systems. As digital technologies get faster, smaller, cheaper, and more powerful, demand will only grow for integrating human and robot interaction. But, while technologies can change on a massive scale in a short amount of time, humans don’t. AI systems that are dependent on real-time analytics offer relevant and personalized experiences. Add to that the rise and proliferation of mobile and connected devices as well as the associated data used by AI systems to deliver actionable insights, it’s no wonder Big Data and business analytics will see such a strong impact over the next two to seven years.  Analytics Are Key Digital technologies are no longer “nice-to-have”, they are “must have.” Knowing and understanding Web Analytics is key to automation in the digital age. It’s not a matter necessarily of getting the information faster; it’s about taking the information and developing actionable insights faster. Businesses that lag behind digitally may find their markets overturned. While those leaders who embrace and focus their digital strategy will succeed in the universal transformation. Having a clear vision and digital strategy is critical to the success of any enterprise wishing to compete. No longer can businesses wait to see what will happen. Their actions can affect revenue growth and cost savings, particularly as their digital leadership relates to their clients and customers. Data is infused within every aspect of business and our daily lives. Forward-looking leaders can’t afford to overlook the emerging trends in AI and analytics in 2019.  If you’re interested in big data and analytics, we may have a role for you. We specialize in junior and senior roles. Check out our  current vacancies or contact one of our recruitment consultants to learn more.  For our West Coast Team, call (415) 614 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast Teams, call (212) 796 6070 or send an email to newyorkinfo@harnham.com.

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