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As buzzwords go, big data is currently one of the most powerful—and one of the most perplexing. It sounds like something only multinational conglomerates can afford. But the concept of analyzing very large amounts of data and looking within it for patterns, trends, and insights is one that nearly any business, large or small, can use to help make better decisions.

The big data you might not know you have

The key word in “big data” is big: The more data you have, the better it works. Want to gain insights into your finances? A few hundred sales records might tell you something, but a few million will turn up more trends and help you gain a deeper understanding of where your money is coming from. Want to get a bird’s-eye view of your customer base? Thousands of customers and prospects fed into a big-data tool will be more valuable than an analysis of, say, your top ten buyers.

How small companies are profiting from big data

The goal of any big-data effort is to improve your business. If you’ve traveled through a major airport lately, for instance, you’ve probably seen Vino Volo, a small chain of wine bars that can now be found in 28 airports. Vino Volo is using big data in the form of a mobile app developed by Punchh, which works as a loyalty program and referrals system. Punchh co-founder Sastry Penumarthy says Punchh “crunches lots of real-time data from mobile, social, and POS to automatically provide brands (in real-time) 360-degree insights about their customers and stores, including visits by location and time of day, orders including specific menu items, reviews and sentiments of reviews, and campaign response rates,” among other insights.

Riviera Partners uses big data for recruiting. The job placement company keeps a huge database of potential candidates that is constantly being updated. Searching this database for the right candidate involves not merely searching for keywords on resumes but by aggregating its own data on a candidate and cross-referencing it with public information (like LinkedIn profiles). Candidates are then scored based on all of these factors on a job-by-job basis before being further vetted and presented to the client.

How can your small business use big data?

If you’re a typical small business, just crunching along from day to day without any real strategic direction, the ability to finally get your arms around your business by digging into the data you already have probably sounds enticing. But big-data service providers don’t make it easy. There are literally hundreds of companies out there, all of which promise to open your eyes to your company’s future by “harnessing big data.”

These companies can be wildly dissimilar. For example, Tranzlogic provides a Web portal for merchants where they can track sales, how various locations are performing, and whether promotions are paying off. It uses “big data” analysis of your credit card transaction data to do this. Or consider MaxxCAT, which makes a network appliance and accompanying software to pluck data from your internal servers and hook those results into processing systems. It’s also a big-data service, but the two companies couldn’t be more different.

Knowing what kind of big data service to work with depends on the type of data you’re looking to analyze.

Big-data companies vary widely in scope and scale. This overview will help you understand the types of companies out there. Some of them are large-scale providers that can analyze data from a wide variety of sources. Others work in extremely narrow niches. Again, choosing a big-data partner depends entirely on the data. There’s no sense in signing with a provider that specializes in slicing and dicing Salesforce databases if you don’t use that system.

InsightSquared: This service is designed to analyze sales and the selling process, with a distinct focus on hooking into Salesforce and similar apps to examine your CRM database. You can further refine this by adding in data from QuickBooks, Zendesk, Google Analytics, and other sources. InsightSquared provides sales forecasts, a pipeline visualization, a marketing cycle report, and more. Pricing starts at $99 per month.

Canopy Labs: Canopy is designed to predict customer behavior and sales trends, offering a variety of scenarios for the future that you can use to help guide marketing and promotional efforts. (For example: Should you target loyal customers or try to bring back those who haven’t shopped with you for a while?) Supports Constant Contact, Salesforce, MailChimp, and more. Pricing ranges from free (up to 5,000 customers) to $250 per month (up to 100,000 customers).

Radius: A big-data tool primarily used to help identify sales targets and aid with lead generation, especially for businesses working with a large number of prospects. A big focus is correcting outdated customer information, so sales reps don’t go calling on shuttered businesses. The company says it aggregates data from more than 30,000 sources. Pricing is $99 per user per month.

Qualtrics: Big data comes to customer surveys, such as those “Tell us how we can do better” pop-ups you get at the end of a Web browsing session. Insights driven by Qualtrics can help with product and market research, ad testing, and even performance evaluations at the office. Pricing varies.

Qualtrics online survey platform helps with everything from product research to performance evaluation.

However, if your business decides to embrace big data, it doesn’t have to mean making a huge commitment to a service provider—contractually or financially. Identify one problem area—sales, finances, Web performance, etc.—and start mining your data for insights. In no time, you’ll be turning big data into big opportunity.

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How Small Businesses Look To Leverage Big Data And Data Analytics

  Benefits of Big Data for Small Businesses Following are key benefits of big data for small businesses- 1. Quick Access to Information Big data makes the generated information available and accessible at all times for the businesses in real-time. Various tools have been designed for capturing user data and thus, businesses can accumulate the information in terms of customer behavior. This huge chunk of information is readily available for the businesses at their disposal and they can implement effective strategies for improving their prospects. 2. Tracking Outcomes of Decisions Businesses of any size can gain huge amounts of benefits from the data-driven analytics and this calls for the deployment of big data. Big data enable businesses to track the outcomes of their promotional strategies and giving the companies a clear understanding of what works well for them and improves their decisions to gain better results. Small businesses can tap on this information to know which of their brands are being perceived by their key customers. Based on this information, businesses can carry out accurate predictions regarding their techniques and at the same time minimize their risks. 3. Developing Better Products and Services Small businesses can use big data and analytics for determining the current requirements of their prospective customers. Big data can help in analyzing customer behavior based on their previous trends. A proper analysis of customer behavior and its associated data helps businesses to develop better products and services based on their past needs. Big data also determines the performance of certain products and services of the company and how they can be used to meet these demands. Big data now also allows the companies to test their product designs and determine flaws that may cause losses in case that product is marketed. Big data is also used for enhancing after-sales services like- maintenance, support, etc.  4. Cost-Effective Revenues   How Small Businesses Use Data Analytics •  One of the key applications of machine learning for small businesses is by using it for tracking their customers at various stages of the sales cycle. Small businesses have been using data analytics for determining exactly when a given segment of customers are ready to buy and when they’re going to do so. •  Data analytics are also used for improving customer services. Machine learning tools are now able to analyze the conversations taking place between the sales team and customers across various channels. These can provide greater insights into some of the commonly faced issues by the customers and these can be leveraged for ensuring that customers have a great experience with a product/service/brand. •  Data analytics have been providing the SMBs with detailed insights on operational aspects. Data analytics can be of great use when it comes to a detailed analysis of customer behavior. This, in turn, allows the business owners to learn the motivating factors for the consumers to buy products or services. This is of great value as the SMB owners can utilize this information for identifying the market channels to focus in the coming time and thus saving on the marketing spend and thus increasing the market revenue.   Data Analytics Trends in 2023 for Small Businesses 1. Emergence of Deep Learning We have been generating huge volumes of data every day and it is estimated that the humans generate 2.5 quintillions of data. Machines have become more adept and deep learning capabilities are continuing to rise in the coming time. Often considered as a subset of machine learning, deep learning uses an artificial neural network that learns from the huge volume of data. Its working is considered to be similar to that of the human brain. This level of functionality helps the machines to solve high and complex problems with great degrees of precision. Deep learning has been helping small businesses in enhancing their decision-making capabilities and elevating the operations to the next level. Using deep learning, the chatbots are now able to respond with much more intelligence to a number of questions and ultimately creating helpful interactions with the customers. 2.  Mainstreamed Machine Learning 3.  Dark Data Dark data is used for defining those information assets that the enterprises collect, process or store but have failed to utilize. It is that data that holds value but gets eventually lost in the middle. Some common examples of dark data include- unused customer data, email attachments that are opened but left undeleted. It is estimated that dark data is going to constitute 93% of all data in the near future and various organizations look to formulate steps to utilize it.

How Big Data Can Secure User Authentication

How Big Data Can Secure User Authentication

Current Trends:

A combination of traditional password and multi-factor authentication system is being given to users, but multi-factor authentication system is optional because many users find it inconvenient.

Two-factor and multi-factor authentication have limited user acceptance.

Many companies have started using user’s fingerprints, voice and face recognition to authenticate the user.

Big data builds user profile without the user knowing about it. The profile is regularly updated and used to authenticate the user.

Various Working Processes

Irrespective of various new authentication systems coming up, the main system remains the same, that is, matching user inputs with the available data in the system. The different authentication systems are described below:

Password-based system: The password inputted by the user is usually matched with the encrypted one stored in the database.

Multi-factor system: The system matches multiple passwords with the inputs provided during the access request. Some of them are stored in the database and the remaining are dynamically generated.

Biometric system: The system collects data from a person’s voice, fingerprints or iris and uses that data to authenticate the user. The iris is a thin and circular structure in the eye. It is responsible for controlling the diameter and size of the pupil and thus enables the amount of light reaching the retina. Eye color is defined by that of the iris.

Big-data-based system: The system creates a profile of the user based on the data it regularly collects. It authenticates access requests by matching access inputs with the data in the profile. Any mismatch or deviation from the profile could set off a warning about unauthorized attempts.

However, organizations have been facing some problems:

Financial and technical challenges in moving from purely password-based systems to more secure authentication systems.

The users prefer to avoid layered authentication if given an option.

The user uses a physical keyboard or a virtual keyboard?

The level of security permissions does the user have?

Number of attempts, user takes to enter the correct password?

An average number of system access, a user makes in a day?

Number of times, the password has been reset?

Organizations have been reaping benefits of this approach already. The data authentication system establishes whether the identity presenting a claim is real, and then verifies whether the identification is owned by the person making the claim.


Many organizations have been watching the developments with both interest and caution, especially those deals with a lot of confidential data, like, banking and finance, defense and healthcare.

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How Businesses Can Gain A Competitive Edge With Location Data

Today’s world is hyper-connected, and data is a currency arguably more valuable than any other. By 2023, there will be 27B networked devices in use worldwide, a quarter of which will be smartphones. Integrated within each of those devices is the power of location data, which is enhancing many of the technologies that consumers have come to rely on. Consumers today expect their digital experiences to be not only personalized for their tastes and habits but also tailored based on context – where they’ve been and where they are in the world at any given moment. Understanding, analyzing and leveraging location-based data enable businesses to provide highly personalized experiences that consumers have come to expect. Here are three examples of how location data can help businesses become more competitive.  

Rideshare services

Rideshare is a rising mode of transportation, with companies like Lyft, Uber, Bird, Lime and many others gaining market share in cities worldwide. , user penetration is at 17.8% in 2023 and is expected to hit 23.1% by 2023. Rideshare services rely on two types of data in order to deliver a smooth user experience. The first is accurate point of interest (POI) data, like businesses, restaurants, hotels, tourist locations, and many more. When a rider inputs a destination, they want the app to know exactly where they are and where they want to go, without having to identify individual addresses. Quality POI data, including numerous place attributes, makes that possible. Second is good predictive analytics data, which ensures that rides (or modes of transportation) are available where and when users demand it. What good is a dockless scooter if there are none around when you need to pick one up for a ride to work? In order to provide a good user experience, rideshare apps need to supply vehicles based on forecasted demand – a problem that location data uniquely solves. By understanding human traffic patterns, identifying popular pickup/drop off points, popular times of day and day of the week, rideshare companies can ensure they meet the demands of their consumers.  

Competitive retail analytics

Though 96 percent of Americans browse online, the majority (65 percent) of the average shopper’s budget is still spent in the store. What’s more, don’t make a purchase online because they can’t see, touch and feel the product. Brick and mortar locations are still incredibly important to retailers, and the placement of their stores is critical in the competitive shopping landscape. Sometimes a store visit will be based on convenience – close to work, home, or other frequented areas. In other instances, shoppers may travel a great distance for a store that’s important to them. Location data can uncover these insights, and help retailers in better understanding who is visiting their store, when, and compare foot traffic to competitive stores.  

Site Selection

Understanding nearby building density and business categories, foot traffic patterns and competitor locations is an important factor in making smart, data-driven decisions when selecting a new location for any brick and mortar asset.  

Factual Data

Not all data are created equal. Quantity does not equal quality, and data is constantly changing as the real-world evolves. Stores open and close. People move continuously. Device lifecycles become increasingly short. Curating massive amounts of continuously changing data is no small feat. High-quality data is essential in giving businesses a competitive edge, and location data is among the most powerful available. That’s why Factual offers high-quality places and people movement data to businesses worldwide. Factual’s Global Places data includes more than 130MM points of interest (POIs) across 52 countries in 29 languages, and its Observation Graph delivers movement data from more than 650MM verified devices worldwide.

Pc Survey Of Small Businesses Indicates Optimistic Outlook

A survey conducted by The NPD Group projects that 77 percent of small and medium-size businesses are planning to spend more, or at least the same, on new PC hardware in 2010 compared to 2009 PC spending. The SMB Technology Report suggests that the increased PC spending is a harbinger of a better economy–driven by new business and new hires.

The NPD survey, conducted in April, targeted businesses with fewer than 1,000 employees. The survey received responses from 250 LinkedIn members who indicated that they are IT decision makers capable of influencing PC hardware purchasing decisions for their respective organizations.

More than half of the respondents stated that expected increases in PC purchasing are being driven by new growth and business opportunities, with more than four in ten suggesting that the additional PC hardware will be needed to support new hires. Following years of economic malaise, it is inspiring to see small and medium-size businesses with an optimistic outlook for new business and job creation in 2010.

“PCs are clearly an important target for corporate spending in 2010,” said Stephen Baker vice president of industry analysis at NPD in a press release announcing the SMB Technology Report. “Continuing to maintain and upgrade technology was cited by 70 percent of PC buyers as a key consideration for SMB buying in 2010 after cutting back in 2009. And since most of the pause in buying came from larger firms, 80 percent of firms with more than 200 employees intend to buy PCs in 2010 to help maintain their corporate infrastructure.”

The uplifting survey results are tempered by the continued fragility of the economy for some SMBs. The survey found that 23 percent plan to reduce PC spending in 2010. Of the firms predicting PC spending cuts, 38 percent are reducing spending due to budget cuts, while 18 percent will be cutting jobs.

Baker examined the study in more detail in a blog post, “Digging deeper we saw that PC upgrade intentions are very different by company size. Almost 80 percent of companies with more than 200 employees planned to spend on PCs as part of a long-term plan to upgrade equipment, a clear sign that Windows 7 is creating interest in larger firms. Conversely, only 65 percent of firms with less than 50 employees intended to upgrade for that reason.”

Take that last part with a grain of salt, though. Put in context, it may be a result of the fact that 75 percent of the companies with fewer than 50 employees indicated that they already upgraded in 2009.

Larger organizations–many driven by a philosophy not to adopt a new OS until it reaches SP1–are ramping up to embrace Windows 7 in 2010. The push to Windows 7 may also be a result of the clock ticking down on official support of Windows XP from Microsoft.

As more enterprises deploy Windows 7, PC hardware sales and Internet Explorer 8 market share will both increase accordingly as well.

You can follow Tony on his Facebook page , or contact him by email at . He also tweets as @Tony_BradleyPCW .

The Big Chill: How To Cool A Small Server Room

Professionals in the computer business are used to dealing with the many challenges associated with cooling servers and other computing equipment. And even they have a hard time.

Now consider the plight of average small business owners. No matter what line of business they’re involved in, they’ve had technology thrust upon them. Servers, networking gear and storage hardware have become a fact of life for even the smallest firms. Most business owners typically set up these machines haphazardly as needed, and that can lead to trouble.

How wrong can a small business go when it comes to cooling its gear? Chip Nickolett, a consultant with Comprehensive Computing Solutions Inc. of Wisc, has seen it all: overheated computers systems locked in closets without ventilation; a fortune squandered on AC in an improperly sealed server room; and a beautifully cooled server room overheating every night because the building manager economized by turning off the AC in off-peak hours.

“Most people haven’t experienced a major failure and just believe that somehow everything will be fine,” said Nickolett. “Usually they don’t pay attention until they experience a big outage, lose data, or have to replace an entire system – only then are they very receptive to best practices.”

Cooling Best Practices

There are, of course, a litany of best practices that data centers have applied for years, many of which apply to small server rooms and closets. This includes: arranging servers in rows so that the cold air comes in the front and is expelled out the back; keeping the doors to the room closed; ensuring that the flow of cold air makes it to the equipment; having redundant AC – if one unit fails, another takes over; and more.

Bob Spengler, product manager for Liebert Precision Cooling, at Emerson Network Power, laid out specific tips relating to equipment rooms under 500 square feet. Number one on the list is to avoid using AC systems designed for humans – known as comfort AC. This, he said, is probably the number one failing in small business cooling – next to not having any cooling at all.

“Cooling equipment needs to be specifically designed for computers and have adequate temperature and humidity controls,” said Spengler. “If you don’t control the humidity level you either end up with damaged equipment due to static electricity or servers dripping with water due to condensation. Also, it can cost about 50 percent more in operating costs if you try to make do with a comfort cooler.”

Another best practice is to seal off the space where equipment operates. That means: no open windows or doors; no missing ceiling tiles: no cracks where air can escape such as between ceiling tiles, under doors or where piping comes through a wall; and shutting off the ducts and vents from the existing comfort AC system – you don’t want the two AC systems mixing. The more control you exert over the air in your server room, the fewer surprises you will experience. 

“Opening a window to let the heat out of a small space that contains a few servers is wrong since you have no control over the humidity,” said Spengler.

Tight control of temperature is also a vital factor in equipment uptime. It isn’t common knowledge, but temperature changes affects equipment reliability. For every 18 degrees F above 70 degrees, electronics reliability is reduced by 50 percent. Therefore, it is best to set the AC to run at around that level or just a little higher – no more than 77 degrees. 

The next point to avoid, if possible, is mixing people with a lot of computers. That adds heat to the space and puts a lot of strain on the AC and the servers. So place your servers and other equipment in a closet or small room in order to create a tightly controlled environment.

For companies with several server racks, it is vital to ensure the cold air actually gets to where it is needed and doesn’t mix with the hot air being shoved out the back of the server. You can have a situation, for example, where you are pumping enough cold air into the room, but it isn’t getting to the top of the racks.

“Eighty percent of failures due to heat will be found in the top third of the rack,” said Spengler.

He recommends the use of blanking panels on the front of the rack to cover the spots where servers are missing. Without this, cold air runs through to the back of the rack and into the hot air at the back, rather than making its way up to the top of the rack. In situations where there is a whole rack sitting empty, you can put blocker panels at the front to prevent any cold air getting in.

Growing Threat

International Data Corp. (IDC) has been tracking data-center power and cooling issues for years via an annual survey. And small businesses are suddenly in the spotlight.

“Smaller installations such as server closets and rooms register highest in terms of cooling issues,” said Jed Scaramella, an analyst at IDC. “There are some very easy solutions customers can adopt such as blanking panels between racks to improve air flow.”

He recommends that small businesses call in outside help to figure out their cooling needs as there are too many ways to get it wrong. And the results can be disastrous. “Consider the expertise of a third party service provider,” said Scaramella. “With space and thermal issues, it is somewhat of a science that goes into running a computer room.”

Drew Robb is a Los Angeles-based freelancer specializing in technology and engineering. Originally from Scotland, he graduated with a degree in geology from Glasgow’s Strathclyde University. In recent years he has authored hundreds of articles as well as the book, Server Disk Management by CRC Press.

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