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Technology plays a fundamental world in every area – and the medical field makes no exception. There are many ways in which the medical field is likely to change, due to the use of technology. And today we’ll talk about some of the most noteworthy transformations we’re likely to experience in the foreseeable future.

Diminished Costs

Did it ever occur to you that technology could actually reduce the expenses in healthcare centers? But how can it do this? By using predictive analysis, this could anticipate the costs associated with admission rates, while contributing to more efficient staff allocation. Consequently, this will allow hospitals to maximize their investments.

Treating High-Risk Patients Better

It goes without saying that high-risk patients require attentive, continuous care. And the good news is that, through the implementation of digitalized hospital records, the data will become readily accessible to medical practitioners. This way, they will be able to establish patterns and links among patients. This understanding might result in better treatments.

Eliminating Human Errors

Humans make mistakes. We always do our best to avoid that. In spite of that, making mistakes is inevitable, because we aren’t perfect. It happens for medical professionals to prescribe wrong medicine, or dispatch a specific medication by mistake. And these mistakes have either short-term or long-term repercussions.

On a different note, it is quite common for people to assume that workman’s comp doctors are less qualified to do a job. Still, this is far from being the case – as it depends on the doctor.

That being said, Big Data can dramatically decrease the likelihood of errors, which could happen with any specialist, for a change. That’s because technology can be used in order to analyze user data and, therefore, prescribe the correct medication to each particular patient.

Concurrently, technology can authenticate the data and point out of place prescriptions.This way, it can eliminate the likelihood of error and supposedly save lives. On a different note, it could be argued that this type of software can be really efficient for physicians who have numerous patients per day.

AI Can Help with Treating Diseases

It is a truth universally acknowledged that some health conditions make it really difficult for doctors to establish a diagnosis and to come up with an effective treatment. Nevertheless, artificial intelligence can do something in this respect, as well. That is to say, technology can be used for surfing through significant amounts of data within seconds, and come up with the right treatment for each condition. Therefore, technology can provide specific, customized solutions to isolated cases.

Health Tracking

Another important way in which the medical field is likely to change is through health tracking. That is to say, technology is making it very easy to track people’s health status and assist them accordingly. Thanks to this, potential diseases could be anticipated and prevented.

To sum up, these are some of the ways in which the medical field is bound to be transformed. The world is continually changing, and we should understandthat this is necessary for development.

The post 5 Ways Big Data Is Transforming the Medical Field appeared first on SmartData Collective.

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If you have any sort of analytics system in place right now, then you’re more than likely not getting as much value out of it as you could. Data monetization refers to the way that companies are able to get real financial benefits out of data sources that they already have.

You might be collecting location information from consumers who use IoT (Internet of Things) sensors or your mobile app if you’re involved with any kind of next-gen web company. Even traditional businesses are collecting more data about how consumers search for and find products and services they’d like to purchase.

By leveraging this data against the traditional databases you probably already have, you might be able to streamline your operations and find revenue streams you didn’t know existed.

Monetizing Big Data on the Largest Levels

Many of the world’s largest tech companies are no longer focused on optimizing costs so much as they’re geared toward delivering the best user experience possible. These firms are looking to collect behavioral data during regular customer interaction with their products. Proprietary data collected in this fashion is legal to use, as is information that companies collect from monitoring social media and the way clients use their web pages.

Researchers perform analytics to draw insight from this data. Once they’re done, large firms develop a plan of action to add new methods of customer communication that streamline the experience. Some firms have opted to go with triggered notifications in apps or on their sites that help to convert leads into actual sales. Others have completely refocused their campaigns because they found that the previous methods they used for promotion just didn’t work.

Blockchain is a Link for Big Data Processors

Blockchain has become such a buzzword that many media personalities now use it incorrectly. It refers to a huge linked list of records organized into blocks that are linked together with a cryptographic hash. This helps to prevent tampering, which means data stays put once it’s written.

Peer-to-peer networking systems are used to reduce the processing load on machines with blockchain ledgers deployed on them. While this technology was originally developed for use with cryptocurrency platforms, it’s inadvertently created a system where content creators are able to sell content without needing a central authority to monitor it.

This means the companies that create large amounts of data are able to profit from it directly by cutting out the middleman and selling it right to firms who need it. One company used it to produce massive databases full of 3D images that online retailers and VR developers can use. They’ve been able to set their own prices and haven’t had to transfer a single dime to an outside conglomerate. Other companies specialize in combining Big Data and Blockchain to bring new insights and increased profits to businesses, while also offering all the benefits of decentralized systems.

Financial institutions are now putting the technology into play as well. Those who’ve adapted to it have been able to deploy much simpler server infrastructures to manage clearing information than those who continue to use traditional methodologies.

SMBs Stand to Benefit More than Anyone

You might be saying to yourself that none of this applies to you because you don’t have an operation that’s as large as any of these examples. Email monetization can benefit even the smallest companies, since it leverages data collected through the least expensive avenue possible.

If you’re asking yourself what is email monetization, then you might be surprised that your company is already probably doing some form of it. Anyone who maintains a database of leads and uses it to reach their consumers directly are monetizing their email list.

Small business owners can benefit from changes in how they look at this data more than anyone else. They have the most room for growth, after all.

Plug your existing email data into a low-cost analytics engine. Find out which of your email campaigns did well and which didn’t. Replay your best campaigns to leverage past success. If you’re an established authority in your field, then you might even be able to get people to subscribe to premium content in this way.

Another great example is advertising platforms. The competition for this is huge, since modern methods are super-precise. Forget about the annoying popups of the previous decade – modern-day ads target very specific demographics and change based on various factors, like geographic location, for example. Data that feeds the popular ad platforms is the new oil – everyone wants some, and the prices are through the roof.

Data Monetization Builds Networks

Take a good look at all the links you’ve collected in your database while you’re at it. Lists of links like these are where affiliate programs start. Whether you’re managing a small email list or a blog, linking with other people can generate leads and help you turn your data into money.

The post How Data Monetization Can Add Value To Your Analytics appeared first on SmartData Collective.

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Big data is playing a more important role in the future of ecommerce than ever before. Launching ecommerce with big data utilization is helping online retailers in countless ways, including:

  1. Expanding less energy testing marketing strategies. They can use Hadoop tools to extract data and identify correlations without having to manually run data audits on their own. This helps them optimize their marketing campaigns without delving through massive amounts of split-testing data.
  2. Identifying the most profitable ecommerce markets. They can tap endless sources of consumer data to see what products are in demand.
  3. Finding new markets to penetrate. Big data helps ecommerce marketers track regions with the most growth potential.

The benefits of big data cannot be overstated. It is going to change ecommerce forever.

Getting Started Using Ecommerce and Big Data

Ecommerce entrepreneurs are beginning to recognize the incredible benefits of using big data to penetrate new markets and optimize their campaigns. However, they must understand the principles of ecommerce marketing before they can get started. This includes launching an ecommerce site.

Ecommerce has been flourishing for quite some time now. Maybe this is why it has become one of the most attractive industries for people all around the world. If you are interested in starting an ecommerce business, you should know that your most important asset is your ecommerce website. At the same time, it is the most important factor that directly affects your business success and revenue.

For many of you, launching an ecommerce site may as well be launching your first website ever. Once you are done setting up your business plan, you might feel confused, not knowing where to start or which problems to address. This is why we have decided to provide you with a list of 5 technicalities to consider before launching an ecommerce site.

Come up with a Domain Name

The domain name gives your online business its unique identity. If you already own a brick and mortar shop, you already have a business name. If this is the case, you need to use one of the free domain availability checkers online to see if the name is available for use.

If you don’t own a physical store, you will have to come up with a domain name for your business. It will be your business’s online identity and it would be wise to consult digital marketing experts on this one. Once you have a few options written down use the tool that we’ve mentioned above to check the domains’ availability. Once you’ve decided which one you want, register for it.

Now, you will need to get web hosting.

Choose your Web Hosting Well

Web hosting is the name of one of the most popular services online. Web hosting service providers are companies specializing in providing technologies and services needed for a website to be accessible via the Internet.

Going with some of the most reputable web hosting companies is essential for your success. Why? Because a good company will make sure that your website has no downtime, and that it loads fast, and they will offer you 24/7 customer support should you need it.

Today, you can choose options like shared hosting, cloud hosting, VPS hosting, and dedicated servers. With so many hosting options, you might easily get confused. The most commonly used ones are cloud hosting and VPS. HostGator, one of the most renowned web hosting companies, has a great guide to help you determine the winner in the cloud hosting vs VPS battle.

Choose an Ecommerce Platform

An ecommerce platform is the next thing you should get familiar with. There are several options that you can choose from: an ecommerce website built from scratch or any of the existing platforms prebuilt to support the ecommerce business model, including WordPress, WooCommerce, Magento, Ubercart, and VirtueMart.

Each one of these may require specific web hosting services which is why you should always closely look at what web hosting services providers offer. As you might have already guessed, each of these options will also dictate how much money you have to invest in website development.

The other aspect that you have to address is website maintenance. Some platforms are really complicated for maintenance and may easily require you to partner up with a web development firm. While the others can be set up and maintained with minimal technical requirements, deeper customization will put you in a position to hire a developer. You can find a more detailed description of popular ecommerce platforms here.

Plan Customer Support in Advance

Customer support is crucial for ecommerce. You have to plan your customer support efforts in advance because they will dictate the changes you need to make on your website.

Live chat software, for instance, is the most popular option in this niche. It enables you to proactively engage potential customers as they arrive on your website. On top of that, it is very convenient for customer support agents who can, thanks to it, serve multiple customers at a time.

Get Ready to Rely on Big Data

Leveraging big data in the ecommerce industry has become a must. With so many competitors fighting over one and the same slice of the market, big data analytics are the only way to stay ahead of the competition. Big data can help you personalize your offer, optimize pricing, predict trends, and more. This is why you should learn big data ecommerce tricks to maximize your sales.

These are the 5 technicalities you have to consider if you want to successfully launch your first ecommerce website. Web hosting, big data, and ecommerce platforms are the most important here. This is why we encourage you to continue your search online and learn as much as you can about the available options.

Ecommerce is Changing the Rules of Big Data Forever

Big data is changing the ecommerce market in fascinating ways. Savvy ecommerce entrepreneurs are going to take the time to understand the role it can play and find creative ways to utilize it to boost their ROI and streamlining their business models.

The post 5 Steps To Launching eCommerce Stores That Are Ready For Big Data appeared first on SmartData Collective.

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The evolution of the IOT has changed the world in countless ways. Many people are still struggling to adapt to it. One of the biggest learning curves that most people face is trying to understand the security vulnerabilities that the IOT network faces. Unfortunately, SQL injections can be an even bigger danger to the IOT than traditional networks.

Anybody that uses devices that are connected to the IOT must be aware of these risks. IOT developers must also take appropriate precautions to ensure they are properly secured. Many security experts argue that resolving any security vulnerabilities that expose any IOT devices to an SQL injection attack needs to be a top priority. The most common way these devices are hijacked is if the hacker used an SQL injection to gain control of a smartphone that controls these devices. This is a problem with IoT devices that are controlled by WeMo smartphone apps.

Some devices are more susceptible than others. Cameras are most at risk, because they can be hacked and turned into spy systems. Smart locks are better secured, but still need to be protected.

Why SQL injections are such a serious threat to IOT devices

In order to completely hijack and IOT devices, hackers need to assume root level of control of it. One of the easiest ways for them to do this is by using an SQL injection.

The scope of this risk is still being appraised by leading security experts. However, they have released preliminary findings suggesting that SQL vulnerabilities can have a devastating impact on IOT networks.

A number of botnets have been studied carefully. They exploit several different security vulnerabilities, but those that allow them to initiate SQL injection attacks are among the most common.

One IOT worm known as Hajime claims to be fighting this epidemic. The anonymous developers of the Hajime worm claim that their creation is programmed to hunt down malicious networks and block them from infecting other devices. It operates by identifying seemingly vulnerable IOT devices and patching the flaws that expose them to being hijacked by an SQL injection.

So far, Hajime seems to be delivering on its promises. The self-proclaimed vigilante worm has assumed access to over 300,000 IOT devices and updated security patches to thwart SQL injection attacks.

As altruistic as this sounds, security experts caution against trusting Hajime. They still don’t know exactly what the worm really does. It is possible that it has a more sinister motive and is being disguised as a vigilante application to keep people off their guard. Even if the application does what it is claiming, it could inadvertently replace some SQL injection vulnerabilities with others.

Nevertheless, the Hajime has helped highlight the severity of the risks that SQL injections have created.

How can developers prevent SQL injection attacks against IOT devices?

IOT devices are difficult to secure for a number of reasons. One of the biggest concerns is that these devices need to be able to be accessed remotely, which means they cannot be shielded with a firewall.

This leaves IOT devices exposed to many types of attacks that would easily be thwarted by desktop or mobile devices. Due to the dangers of SQL injections, they need to be one of the biggest concerns.

What measures can be taken to address these problems? Since SQL attacks are designed to take root control of a device, having an anti-root feature in place is one of the best ways to secure the device. This will identify any attempt to access the root level controls. If such an attempt is made, the device can lock out any intercepting traffic.

This would make it much harder for a hacker to coordinate an SQL injection attack. They would need to:

  • Decompile source code of any vulnerable apps used on an IOT device that they could penetrate
  • Get rid of any SSL pinning functions and anti-root features
  • Compile the app again
  • Manually or remotely reinstall it on the device

This would be a very cumbersome process. Some hackers would have the dedication and fortitude to go through with it. However, simply equipping all vulnerable apps with anti-rout this would be a very cumbersome process. Some hackers would have the dedication and fortitude to go through with it. However, simply equipping all vulnerable apps with anti-root functions would be enough to deter at least 90% of would be hackers from launching SQL injection attacks.

The post Assessing the Severity of SQL Injection Threats to IoT Security appeared first on SmartData Collective.

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The GDPR (General Data Protection Regulation) was developed a few years ago to replace the Data Protection Directive of 1995 in the European Union. After years of revisions, it finally took effect in May. The regulatory framework was enacted to protect the privacy of EU citizens, with GDPR fines and other regulations helping to maintain the rules. It is a noble goal and will likely have a number of positive benefits. However, it may also create a new set of risks that security experts and crisis management teams will need to prepare for. One of them is the likelihood that GDPR ransomware threats are going to rise.

Will the GDPR put companies on high alert about possible new ransomware attacks?

Ransomware has become a very serious threat. According to CSO Online, the global costs exceeded $5 billion in 2017. A number of factors have played a role in driving the explosive threat that it poses to organizations of all sizes.

Most laymen wouldn’t attribute the GDPR to an increase in ransomware attacks. However, some of the most astute cybersecurity experts have made this link. The potential for GDPR extortion is worth putting on your radar.

Trend Micro is one of the most prominent organizations to make such a bold prediction. According to a speculative post they published last December, a growing number of ransomware attackers are going to calculate the likely fine a company would face under the GDPR before issuing their demands. They will probably set their ransom demands just under the penalty threshold they would face. The likely outcome is that many companies would make the payment and never report the incident, for fear that EU regulators might find out and impose GDPR fines on top of it.

Other experts have claimed the opposite is likely to occur. They cite a provision in the GDPR that requires organizations to report any security breach, even if the impact is minimal. However, the likelihood that they will follow through on reporting could be low, regardless of the merits of the law.

Some organizations may decide that the risk of being fined is greater than that of quietly breaking the law and sweeping a GDPR ransomware incident under the rug. Also, they may make the argument that the ransomware infection does not qualify as an actual security breach. Some lawyers could argue that ransomware generally locks devices or freezes servers, but does not actually purloin encrypted data, therefore it would not actually qualify as a breach and does not need to be reported.

These threats may be especially effective against very small and home-based businesses. Unfortunately, a growing number of malicious actors are targeting these types of businesses, and GDPR extortion is plausible.

VPNFilter malware attacks are among the biggest threat to home-based businesses. They are specifically designed to infect home Internet routers and small office networks. According to the United States Computer Emergency Response Team, this type of attack has created a number of risks in addition to malware, including:

  • Temporarily or permanently destroying sensitive information
  • Disrupting operations by crashing the network
  • Forcing organizations to spend thousands of dollars or more on file and system restoration
  • Potential causing irreparable harm to the company’s image after the attack was orchestrated

This can be a huge concern for businesses of all sizes. GDPR ransomware attackers realize that home businesses cannot afford anywhere near the fines that the GDPR calls for and will act accordingly.

Organizations must take sensible precautions to avoid this dilemma

Ransomware attacks are likely to increase in the coming years, especially as EU regulators become more stringent about enforcing their policies. Organizations of all sizes must recognize that they may be put in a place where they need to choose between paying the ransom or accepting a fine for failing to meet compliance standards. The regulators may act with leniency, especially if the company is small. However, they should not operate on the assumption that they will get off with a mere slap on the wrist. On the other hand, they should consider the possibility that malicious hackers may continue to organize such attacks as long as they feel there is a chance that the company is in violation of GDPR requirements.

The only guaranteed solution is to make sure the network is strongly defended to prevent a ransomware attack—or any subsequent GDPR extortion—in the first place. Here are some precautions that can help them.

Reset your router

The VPNFilter attacks were organized against businesses with routers that had not been updated for quite some time. Resetting the router could significantly reduce the threat of these attacks. Of course, there are other forms of malware that exploit other vulnerabilities. However, fixing all weak points in your security infrastructure is key, so it is important to address every possible port through which a ransomware attack may be carried out.

Understand the importance of IoT management

According to Cloud Management Suite, securing IoT devices is one of the most important steps to prevent ransomware attacks. Recent figures show that 10% of ransomware attacks against SMBs are targeted at IoT devices. They should keep the IoT network architecture as simple as possible and regular monitor all incoming and outgoing data on all IoT devices to look for threats.

Make sure that software is regularly patched

Hackers take time to understand the flaws in every application they can exploit. The older an application is, the more time they will have had to uncover them. This leaves you vulnerable to attacks. Make sure that your software is patched to prevent this from happening.

Make sure that your data is regularly backed up

Since most organizations carefully encrypt their data, they are not so worried about hackers stealing and releasing it. Although some ransomware attacks do this, the majority threaten to destroy files instead. You can nullify their threat by making sure that your data is carefully backed up on another server that they will not have access to.

Have automated content scanning controls in place

It is vital that you regularly scan incoming emails for all known malware threats. Email is one of the most common ways to distribute malware.

Be very careful using public Wi-Fi connections

Hackers often spoof hotspots to trick people into providing information through them. Make sure that you carefully verify any hotspot that you’re using to prevent them from getting access to your machine.

Remain Aware to Stay Safe

While the threat of ransomware is never fun to think about, it doesn’t need to rule your life either. It’s simply a matter of being as aware as possible and taking whatever precautions you can to decrease your odds of getting hacked, and to keep your data secure. Hopefully, GDPR’s benefits will far outweigh the risks.

The post GDPR Fines, Ransomware, and Cybersecurity: What You Need To Know appeared first on SmartData Collective.

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According to some experts, the origins of virtual reality can be traced back to the 1950s, although the first virtual reality display wasn’t invented until 1968. The field has obviously evolved over the past half of a century. However, it is changing more rapidly than ever before. Some of the biggest reasons for the sudden evolution are the recent milestones in the combination of virtual reality and machine learning.

Last December, Emory Craig, a well-known technology evangelist, writer, and speaker on machine learning, wrote a Quora post that stated that the role this technology will play is going to be even more significant in the very near future. Craig argued that deep learning could be a tremendous game changer for virtual reality by 2020. In the meantime, machine learning and artificial intelligence are already impacting the field in spectacular ways.

Craig provided a very helpful synopsis on the subject. Jack Clover, a computer vision and NLP expert for Logikk, delved deeper into the relationship between machine learning, artificial intelligence and virtual reality in a recent post on LinkedIn.

Clover points out that at its core, artificial intelligence is a term that describes an algorithm that pulls from its own knowledge base to deliver outputs that have a tangible impact on human users. With this concept in mind, it is easy to understand the relevance of machine learning to the field.

The connection to virtual reality becomes clearer when you consider the growing importance that artificial intelligence has on it. Clover points out that a simple headset that displays digital images doesn’t require any form of artificial intelligence. However, virtual reality does depend on highly sophisticated AI algorithms to emulate reality.

VIOND has highlighted a number of ways that machine learning is changing the field. Here are a few of the biggest.

Hand and eye tracking

Most of the discussions I have seen about improvements in virtual reality focus on the ability of the simulation to replicate the environment that users immerse themselves in. However, the simulation’s ability to track the movement of its users is just as important.

Deep learning is becoming more adept at understanding the millions of possible poses that people can make with their hands. It is also able to track patterns of human eyes with greater precision than ever before.

By better understanding the mechanics of human inputs, virtual reality applications will have a better understanding of their intent. While developing better ergonomic controllers is helpful for reaching this goal, machine learning is proving to be even more effective.

Detailed environmental mapping

Virtual reality can better simulate an environment by replicating one that is already in existence. They can use external structure sensors with an AI system to create a mixed reality experience for their users.

Many of these applications depend on fledgling systems. The systems are already being used to simulate experience in their own users’ homes. They can identify the positions of furniture and construct a virtual model of every room with exceptional spatial detail.

The applications for this are limitless. One person could use a virtual reality set to navigate an area to construct a virtual map. This could be used to help other people familiarize themselves with the environment. It could be incredibly useful for helping blind people understand the obstacles they may encounter while navigating a new environment.

Incorporate voice commands into training simulations

Voice commands can also be very useful in training simulations. The virtual reality simulation can keep track of voices for people in a field of view, which will help provide better information for training exercises. They can use the verbal information that people using the simulation provide to better understand warnings, which will be relayed to soldiers that use the simulation for training purposes. They can also receive recommendations for the types of problems they encounter.

Machine learning is transforming virtual reality

Virtual reality has become far more advanced since its inception. Machine learning is playing a very important role in its progression. What will AI bring next to the future of virtual reality?

The post Virtual Reality And Machine Learning Go Hand In Hand appeared first on SmartData Collective.

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We are living in a data-driven world where Big Data is influencing almost every aspect of the digital marketing landscape. It has proven instrumental in creating customer-centric campaigns. That’s why the growing need for Big Data analytics and top-notch big data marketing strategy is no secret in the business world. In fact, the overall consensus states that those not leveraging the Big Data analytics will be left behind and lose their tactical advantage in the coming years.


However, just because every business should make it happen doesn’t mean that they can. According to the Big Data Executive Survey 2017 by New Vantage Partners (NPV), out of the 85% of companies that are trying to be data-driven, only 37% have been successful. It seems we are finally advancing from the infancy stages of Big Data, but still, plenty of growing pains and roadblocks are being faced by marketing teams.

Here are four of the big ones and ways to push through them.

1. Translating Complex Datasets to the Customer Journey Source

It’s nearly impossible to get fruitful insights from Big Data if you don’t know its correlation with the customer journey. Unfortunately, customers take a myriad of paths and switch between different channels before converting into paying customers. It takes even longer to turn a paying customer into a loyal one.

As a marketer, you will need to have a deeper understanding of a customer’s complete journey from awareness to revenue. That’s why you will have to pull data from all your platforms, both offline and online. For example, a retail store can use data-based POS systems to gather data from stores and tie it up with the data collected from their website and social media.

Naturally, you will need to have an in-depth understanding of different customer journey points, individual experiences, and impact points. Still, you will need to find the hidden correlations between Big Data and the overall customer journey, for which you will need to consider the following:

  • Tap into previously unknown paths customers are taking to visit your online or offline stores.
  • Create and maintain different timelines simultaneously to take appropriate action from your end.
  • Identify different types of sentiments consumers express during the various stages of a sales funnel.
  • Summarize the behavioral patterns based on a combination of individual experiences and interactions with your brand.
2. Data Overload

Data companies have access to a treasure trove of actionable insights. However, this trove is expanding at an unimaginable rate, making it nearly impossible for organizations to make sense of it. The digital universe is doubling in size every two years. By 2020, the data we create and copy annually will reach 44 zettabytes or 44 trillion gigabytes.

When it comes to Big Data analytics, more is anything but merrier. Collecting data is not the hard part, knowing how to apply it is. Unfortunately, in the race to avoid being left behind, most organizations tend to gobble up as much data as they can. But, this approach can quickly lead to data paralysis, a common ailment among companies.

Narrow Down Your Sources

One of the first things you need to do is to take a step back and narrow your data collection sources down as much as you can. Find the minimal essential data sources that your company can rely on to see how your business is doing. Alternatively, you can also collect data concerning a few crucial metrics.

Filter the Data

You will still need to filter the collected data to remove the information that has nothing to do with your business goals. Decide well in advance what does and doesn’t fit into your analytics data stream. Don’t waste your time and labor on deciphering irrelevant metrics.

Focus on Critical Data Patterns

You need to focus on what matters. So, make sure to find and study data patterns that illustrate your goals. Is a sudden rise in Instagram likes worth your attention? Does it affect your click-through rate or translate into new sales leads? Find these correlations and focus on them only.

3. Segmentation


While big-picture data analysis is extremely crucial, your marketing efforts also need to appeal to a wide range of audiences. So, when you incorporate Big Data into the mix, you need to have a granular segmentation process to define and divide leads into designated groups. This will provide you with a clear view of the group(s) that can translate into the most profitable one.

Define the Objective

First, you need to define the objective of the segmentation. How will you use this segmentation? Do you need it to generate new leads? Or perhaps you want push existing customers further down the sales funnel. Whatever your end-goal is, make it clear well in advance to get the best insights into customer behavior.

Identify Relevant Parameters

The next step is to identify relevant parameters. For example, if you are segmenting website visitors, the most relevant parameters would be how long they have stayed on your site, which pages they viewed the longest, which visitors went through more than one page, and their Geolocation, among others.

Granularity and Threshold

Lastly, you will need to determine how you are going to break down the parameters to get the desired insight from the data. Usually, three levels i.e. low, medium, and high are used for granular segmentation. However, you can define your own thresholds.

For example, you can break down the duration of website visitors into: the ones who stayed on your site for less than five minutes, between five to ten minutes, and more than ten minutes. This type of micro-segmentation allows finer targeting of content, offers, products, and services, resulting in substantial returns.

4. Privacy Concerns


Data privacy is perhaps the tallest hurdle in creating a data-driven approach in your company. The Facebook-Cambridge Analytica Scandal was the boiling point for the controversial “gray area” surrounding data collection and management.

To top it off, the General Data Protection Regulation (GDPR) has put severe restrictions on how companies can collect personal information from their prospects. Although it is limited to the European Union, other nations are more likely to take similar steps in future. Besides, many consumers are now extremely cautious about how they share their information on the web.

If you want to get valuable data, you need to design trustworthy data collection strategies. Keep the following in mind:

  • Don’t cut corners. Make sure your entire data collection process works around A-Z transparency and security.
  • Make sure to let your customers know you are collecting personal information, how you are doing it, and what are you going to do with it.
  • You can use first-party data collection methods such as social login and social account linking to collect personal information. It allows your consumers to know what information is being collected and how.
  • Furthermore, you need to put your customers in the driver’s seat and give them the opportunity to control how their data is (or isn’t) used. Gathering person-provided data is one of the best ways to ensure your customers are in the driver’s seat.
Over to You

From planning strategies based on reliable metrics to accurately measuring the results, Big Data has revolutionized online and offline marketing dramatically. But, this astonishing tool comes with a few inherent challenges, ranging from identifying meaningful insights to privacy concerns. However, those challenges should not hold you back from developing a successful Big Data strategy. Hopefully, this article will set you in the right direction. In the meantime, tell us about your Big Data endeavors in the comments section below.

The post 4 Big Data Marketing Strategy Issues Holding You Back (And How To Fix Them) appeared first on SmartData Collective.

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Payroll management

is a function that most companies and employees take for granted. However, it is highly complicated and difficult to run efficiently. This only becomes evident to people after payroll errors surface. A growing number of companies are depending on machine learning and payroll AI (artificial intelligence) to improve their payroll. They can even depend on machine learning when they outsource payroll functions. Preliminary data shows that this technology has been incredibly effective.

Using big data to identify and tackle payroll challenges

A 2014 report from Deloitte uncovered some of the most pressing challenges facing the payroll management profession. The report highlighted some very surprising issues. Around 25% of survey respondents said that their company’s payroll solutions were not properly setup or documented. Nearly a third of participants said that they were still fleshing out their payroll and workforce management strategy, despite the fact that many of the companies had been established for several years.

A number of problems surfaced even among companies that had felt like they had fully developed their payroll management solutions. One of the biggest problems was with tracking employee expenses. Only 33% and 21% of companies tracked domestic and global employee expenses, respectively.

Many companies are just beginning to realize the imperfections in their payroll management processes. They are beginning to invest in new AI technology that can help them address these problems.

Here are some of the ways that machine learning and artificial intelligence are disrupting payroll management.

Enhancing interactivity

Most people think that payroll management companies and departments are isolated from the employees that they serve. This actually is not true. Payroll managers receive frequent queries from customers on an ongoing basis.

Machine learning has helped payroll managers develop more efficient processes for handling these queries. One of the most common ways that they can improve interactivity and streamline customer service is by tracking the questions and responses between customers and payroll managers. After observing a pattern, they can help customer service representatives develop automated responses to the most frequent inquiries.

A number of payroll management and human resource departments have also started using online chat bots to streamline these processes. You can take a significant load off of other people.

Consolidating with other human resources functions

For many years, payroll management was handled separately from other functions within human resources departments. This may same unnecessarily inefficient to the casual observer, but there were logical reasons for fragmenting human resources functions. While function such as payroll management and benefits administration had a lot of overlap, there were also some complicated nuances that made it difficult to integrate them.

Machine learning is helping address this problem. It has helped resolve some of the differences between various HR functions, so they can be administered through the same interface. This helps reduce the head count of human resources staff members, minimize human error in payroll management and HR functions by reducing their burden and make sure that all claims are processed more quickly.

Machine learning is necessary to ensure the complete integration of payroll and other human resources functions, because it can master the details of various processes by observing existing human resources staff members at work.

Identifying irregularities in employee hours and making sure employees are fully paid for time at work

According to the Association of Certified Fraud Examiners, 27% companies have to deal with employees fraudulently clocking in for hours they are not working. There are number of ways that they do this. One of the most common is by getting one of their coworkers to punch their time card for them.

Making sure that employees are paid for the hours they work is also very important. Some employees may forget to punch their time card. They may also want to problems where the time clock didn’t record their entry properly, so they have to worry that they’re ours may not be logged.

Machine learning is likely to help significantly with both of these problems in the future. Algorithms will be able to track activity in the company and tell whether or not an employee was likely present. This will help minimize payroll fraud and ensure payments are made.

The post How Payroll AI and Machine Learning Are Transforming Businesses appeared first on SmartData Collective.

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Marketing has changed immensely in the digital age, with more stress on improving the reach that a company has. Increasing this reach can lead to sales, brand recognition, and overall consumer trust of a small or large company. Social media is the best tool to promote any type of content or engage with customers effectively. This has given rise to social media analytics so marketers can see exactly how content is going over with their community of followers. The marketing industry has now optimized analytics and social media data into usable instruction of how to proceed in the future. The following tips include how to use social media analytics and make use of the data to become more efficient.

Clearly Define Goals

Every company’s social media team might have a different goal for the accounts. For some, customer service is paramount and saving customer relationships is the tangible goal that management has set for the team. For others, establishing a name in a niche or industry is paramount, as it helps legitimize a business that might be new or has rebranded. The data that is gathered can be used to clearly define a goal and a strategy to reach this goal. Lack of understanding of what the main priority of a social media campaign is can lead to waste in spending and an overall lack of results due to having no defined goals.

Optimize Content Strategy

Generic content simply does not work

like it used to, as the marketing world and social media world have been saturated with millions of clickbait type content. For social media, there are a limited amount of characters that can be used in the case of Twitter, so maximizing the draw of these characters is important. Being able to see what type of content resounds best with followers is also important. The other factor of being able to see how many leads were attained through content gives a better idea of how to increase sales, set appointments, and dive into the sales process in a smooth way with a potential customer. Average content does not have any place in the social media world, and social media data can help a social media team continually post engaging content. Social media content experts understand that being concise, clear, and thought-provoking in a post will yield the best results.

Find Influencers That Convert

The world of influencer marketing has erupted over the last year with no signs of slowing down. Finding the right influencer to partner with a brand can be extremely difficult. The trick to finding the right influencer is finding an influencer who has built a sense of community with their followers. These influencers value their followers and only promote trustworthy products or brands. An influencer that seems to promote less than quality brands is not the type of influencer that a company wants their brand associated with. Find a platform that has social media stats for a particular influencer so it can be determined whether the engagement the influencer receives is worth the money that would be paid for a post.

Posting At The Best Time Possible

Far too many companies

do not utilize their social media data to the best of their ability. Something as simple as posting content on social media during a specific time can increase the reach the post has. If a company finds that their posts get the most traffic and engagement in the morning, then they need to publish a post every morning. If they find they have an international community of followers, posting at a time that these followers engage can be important. Setting up scheduled posts will allow a company to take full advantage of posting at the same time every day. Followers that wait for each and every post will look forward to this time of day whether they are reading a tweet with their morning cup of coffee or engaging with a Facebook post around lunch time. Saving posts for high traffic days when the post is of the highest quality can yield great results as well.

Do not go with a gut feeling when it comes to social media strategy, but rather utilize and translate the data into an actionable plan. Social media data can help take the next social media campaign a company runs to the next level!

The post How To Use Social Media Analytics To Increase Your Business Success appeared first on SmartData Collective.

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Cloud solutions are getting popular with enterprises adopting modern cloud infrastructure to move from traditional systems to an agile structure. There are lots of benefits to adapting the hybrid cloud for entrepreneurs. Most of them already have their own private cloud networks, allowing them to collaborate easily, reduce storage costs, and enhance scalable capacity. Tech giants like Amazon, Google, Microsoft, and Oracle along with other small service providers are leveraging the cloud trend too, having built public cloud offerings.

In public cloud computing, service providers make resources like virtual machines, applications, storage, etc. accessible over the internet, offering services to multiple clients using the same shared infrastructure. Whereas in a private cloud, the services are offered behind a farewell, and the servers are exclusively used by an enterprise; information being accessible to its users only.

In the present times, enterprises are moving to a hybrid cloud model which is a combination of both public and private clouds. The hybrid cloud encompasses best features of both of these cloud environments. It promises the control and security of the private cloud and the flexibility and cost-effectiveness of the public cloud. Enterprises are considering the hybrid cloud as an essential and natural evolution from the traditional business models. According to Gartner, by 2020, 90% of organizations will adopt hybrid infrastructure management capabilities.

From affordability to agility, read on to discover why enterprises should adopt the hybrid cloud platform.


As per IBM’s research, 54% of the executives consider lowered cost of technology as the reason for implementing the hybrid cloud. A public cloud tends to be more affordable than a private cloud, and hybrid cloud adopters can balance their needs to be cost-effective.

In the hybrid cloud, enterprises get an option to pay for only the extra cloud space used. There is no need to spend on massive infrastructure and employ maintenance staff. They can instead move some of their computing needs to the cloud. There is only a simple monthly fee structure associated, which proves to be cost-efficient. Enterprises can, therefore, adjust the size of their cloud services based on the demands of the customers or size of the organization rather than investing in maintaining an in-house system.

With less money spent on infrastructure, more funds can be used on the projects meant to take the business forward. As per a study carried out by IDG Research Services in conjunction with Dell EMC, 24% of executives could reduce their average IT cost due to hybrid cloud implementation.


The major challenge facing enterprises with the public cloud is the security of their data and applications. There might be certain applications or some sensitive data requiring a high level of security. They can be stored in a private cloud while the public cloud can be used for added capacity when needed and to store information required for day-to-day operations. Data stays safe since it is hosted internally and accessed through encrypted means with complete data security.

The hybrid cloud, therefore, allows keeping customer data on a dedicated server, helping enterprises to leverage the high performance of the cloud along with ensuring an agile and secure environment.

Flexibility and Scalability

Data is easily available for access from anywhere in a public cloud. A private cloud, on the other hand, facilitates hosting security compliant applications. This ensures flexibility to enterprises looking for both security and mobility.

The hybrid model ensures portability – applications and data can be moved across clouds or your data center with minimum downtime and without causing disruption to employees or customers. The ability to move between the private and the public cloud easily makes this model preferable for enterprises, where they get an agile IT environment and benefits of both the worlds.

The hybrid cloud also offers an opportunity to scale out to a cloud environment for specific workloads. It allows enterprises to scale resources up and down as per their business requirements. They can add new hardware, software, and services whenever needed.


The hybrid cloud model is becoming the ultimate choice for enterprises looking to respond quickly to changing clients’ expectations along with meeting increased compute, networking and storage needs. It enables faster time-to-market for new products and services to attract customers. A hybrid cloud offers the architectural framework for a dynamic IT environment, allowing enterprises to easily handle unpredictable fluctuations in usage and optimize clients’ experience. In times of heavy usage, enterprises can utilize the public cloud to experience fewer outages and less downtime.


Enterprises like having constant R&D to stay ahead of the competition. Conducting R&D, however, costs time and money and requires new IT infrastructure. Moreover, if your idea doesn’t succeed, your resources are wasted.

The hybrid cloud provides a platform where a completely new idea or service can be tested and experimented and then scaled if found successful. With the pay-as-you-go model and increased security, the hybrid cloud offers a perfect environment for testing without any need of arranging for computing infrastructure.


The public cloud sometimes faces the problem of network issues resulting in slow or poorly performing applications. This is specifically visible during peak traffic periods. Enterprises can leverage the private cloud to reduce the inconsistent performance of the public internet, which can lead to an improved user experience. For certain high-speed functions, apps can be run on the private cloud. The hybrid cloud, therefore, allows allocation of computing resources in a more effective way for better connectivity. It also reduces distance-based latency by ensuring that the infrastructure is delivered from users’ nearest location.


The hybrid cloud environment is vital for an efficient strategy that needs different workloads and big data. Key business decisions based on analytics require collecting real-time data from multiple sources and different systems. To fulfill these real-time needs, enterprises require computing power and storage as per their exact needs.

Final Note

The hybrid cloud provides a competitive advantage to enterprises by empowering them to bring changes with agility and enhancing customer experience. However, before adopting the hybrid cloud, it is important to consider factors like individual usage requirements, the sensitivity level of your data, industry regulations, budget, etc.

An effective hybrid cloud strategy can help enterprises to decide which workloads and applications to move to the public cloud and save costs. The hybrid cloud can give your enterprise too an opportunity to innovate new functionalities and resources by striking the right balance between the on- and off-premise computing. One size does not fit all and the hybrid cloud with its ‘mix & match’ agility approach creates an efficient, modular and flexible IT system.

The post The Benefits Of The Hybrid Cloud For Entrepreneurs appeared first on SmartData Collective.

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