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Category Archives: Data warehouse

How big data can increase your profit

One of the biggest, buzziest phrases making the rounds in corporate circles at the moment is “big data”. But what does big data actually mean? What is it and, more importantly, what can it do for your business or organization? The good news is that it’s not just another tired old buzz word that actually has very little meaning (“pushing the envelope”, we’re looking at you!) Using big data within your company can actually help you increase profit. Let’s take a look at how.

So, we’ve established that big data is causing a stir and creating a buzz in companies that are in the know. In fact, it’s become hip to bandy about the phrase whenever one is trying to impress their boss, senior management or fellow co-workers. But like any lingo or jargon that is currently cool, it really doesn’t count for a whole lot if it doesn’t mean anything, particularly in the workplace.

The good news is that, unlike some of the more hackneyed expressions thrown around by those colleagues that are so desperate to impress their seniors, big data does actually mean something. And, more to the point, it can help your business thrive. Big data can help you achieve that end result that everyone in business is chasing: profit.

This is why big data is trending so sharply at the moment – after all, every owner or manager of a small or medium-sized business wants to grow their bottom line. Times are hard in many industries: increasing competition from abroad, the threat of the internet to bricks-and-mortar stores, a difficult economic climate – the list goes on. But what if something as simple as using your business’s data could push you heads and shoulders above the competition, and help turn around that downwards or flatlining arrow on your sales chart and point it upwards in the direction of success?

But before we get to that; what actually is “big data”? Why is it big? Well, we may have said that using data to grow profit is simple but, in actual fact, it’s really not as easy as all that. Big data is used to refer to various sets of data that are so huge and so complex that the traditional methods of processing data are virtually useless. Database management tools and other processing applications become redundant and are just not up to the task of capturing, storing, searching for, sharing, transferring, analyzing, and visualizing data.

Instead of looking at separate small sets of data, big data – as the name implies – looks at larger sets that contain far more information. This enables anyone analyzing the results to cross-check the sets and pinpoint trends, both positive and negative, across the entire business. As a result, owners and managers can make more informed decisions that affect the company in a more beneficial way than is possible by merely looking at small, isolated sets of data.

Big data therefore plays a valuable role in strategy and planning, and also helps troubleshoot worrying or problematic trends that threaten the performance and profitability of the business. Put simply, using big data to assist in making decisions for your company is about being able to see the bigger picture (to use another tired corporate buzz phrase). Decisions made with all the facts at hand will naturally help increase revenue, as opposed to blindly feeling in the dark and making changes to one area or department that may negatively affect another.

There are a number of ways that you can use big data analytics to make better decisions and increase profit. Crucially, it allows you to see what really makes your customers tick. Nowadays many businesses offer different ways for their customers to communicate with them. From email to a website, to phone calls and human interaction, all of these present you with meaningful information about your clients’ behavior. Knowing what your customers rely on you for, how they interact with you, and where they may hesitate or stumble when using your services, provides a wealth of knowledge just waiting to be mined. However, a lot of this data is unstructured and therefore cannot be analyzed using traditional means. That’s where big data comes in: it can help you uncover the information you need to really understand your customers.

Of course it goes without saying that a deeper understating of your customers can help you grow your customer base, increase repeat business, heighten customer loyalty, and reduce bounce rates and the number of dissatisfied customers. But that’s not all – analyzing this data will allow you to develop new products or services, create stronger, more effective marketing campaigns, and create an all-round better experience for the people that matter most – the people you serve.

Want to learn more about big data, and find out how it can have a seriously positive impact on your business’s revenue? Talk to us today – we have the knowledge and experience to help you really get the most out of your company’s intel.

3 things to know about natural language tech

MobileGeneral_Aug04_AIt might all seem a bit too much like something out of a sci-fi movie, but artificial intelligence is quickly becoming a big part of the IT landscape. One segment of artificial intelligence in particular, Natural Language Processing (NLP) – essentially a computer’s ability to take unscripted human words and turn them into something useful – is playing an increasing role in the way we use our devices. Here are three things you probably didn’t know about NLP.

There’s more to Natural Language Processing than voice recognition

Voice recognition might be among the most well-known practical uses of NLP in the technology we encounter in everyday life – but that likely has more to do with the popularity of the services that employ it, like Siri, Google Now and Cortana, than the merits of voice recognition in comparison to other NLP functions that tend to stay out of the limelight.

Truth be told, there’s a whole lot more to artificial intelligence than NLP. In fact, NLP is more effective in analyzing text data than it is sounds, which is precisely why digital assistant apps first use voice recognition to turn your commands into text data, and then use other NLP capabilities to search online for related information.

Natural Language Processing has already moved beyond its infancy

It’s tempting to believe that elements of artificial intelligence like NLP are still in the realm of the sci-fi movies, and that they are a long way from being useful to the technology we use in our everyday personal and business lives. It’s tempting, but further from reality than you might realize. That said, it’s true that to date there has been no commercial use of NLP that has truly exploited its full capabilities; even its deployment in a recently launched project to automate customer service only really scratches the surface.

What is clear is the shape that future uses of NLP will need to take. We already know that NLP alone doesn’t always judge context well, since it needs to learn about its environment first – without turning to other sources, for example, one app employing NLP would struggle to differentiate between providing traffic information and diagnosing a health complaint. The key, at least for now, is to restrict the scope in which NLP operates – by limiting its use to a travel app, for instance, NLP could learn about the various travel arrangements you make and then devise itineraries for you.

It works with more than just large-scale data

While it’s undeniable that NLP can be put to great use in analyzing vast swathes of aggregated information, for example taking masses of social media data and being able to assess the feelings of users towards the subject in question, that’s not the limit of its capabilities. Contrary to popular belief, NLP can also be used to interpret much smaller-scale data in real time. This is where its true value comes into play in terms of being able to take natural-language user input, in an app setting for example, and make decisions that add value to our mobile experience.

Whether for automated customer service or comprehensive sales applications, it’s clear that Natural Language Processing – and other aspects of artificial intelligence – hold the potential to be of value-adding benefit to the business world in the near future. It’s an area that’s very much still in development – and so even more exciting, and important to watch – but now is the time to discover how best to implement NLP technologies into your company. By getting ahead now, you can offer a customer experience that truly sets you apart from the competition. To find out how we can help you achieve just that, and at the same time maximize the value you drive from mobile technologies more generally, give us a call.

This entry was posted in General Articles A, Mobile Phone – General and tagged artificial intelligence, Data, Mobile, natural language processing,  user experience. Bookmark the permalink. Both comments and trackbacks are currently closed.

 

Save energy in your data center

Save energy in your data center

Is your data center sucking up energy? Are 164_Virt_Athe costs of maintaining your server rooms out of control? For many business owners, the server room and data center are foreign lands they’d like to pretend don’t exist. But whether you acknowledge it or not, they could be costing you hundreds of extra dollars every month. Here’s what you can do to reduce costs.

Perform an energy audit

There’s a good chance your IT staff has never once thought about how much energy your server room and data center are consuming. So, the first step to rectifying this problem is to identify just how much power is being sucked up.

To get you started, here are a few questions to ask:

  • How much of the data center’s power budget goes to support systems?
  • How much goes to IT systems?
  • How much IT output do you get for every kilowatt/hour of power sucked up by your data center IT systems?

Answering these questions will help you determine just how efficient, or inefficient, your data center actually is.

Decrease the IT workload

When you save a single watt of energy at the server level, it can result in a total saving of nearly three watts in your data center costs.

So how do you decrease the IT workload? Virtualization is a common and effective tactic. Instead of wasting money on cooling your own servers in your data center, with virtualization you can have them hosted by your IT provider and then their technology delivered to you through the Internet. This allows you to eliminate some of your servers from your office and therefore reduce cooling costs.

For alternate ways to decrease server workload, you can also:

  • Eliminate unused servers
  • Consolidate servers
  • Purchase more energy-efficient technology

Mind your humidity and temperature levels

Because many non-IT personnel are terrified of the data center and simply don’t understand it, often they falsely believe that the room must be kept as cold as the North Pole in order to protect sensitive data. This is simply not true. While it is true that excessively high temperatures, humidity or dry conditions can harm your data, most modern-day data center equipment is incredibly durable and can tolerate a much wider range of humidity and temperatures than in decades past. Because of this, it is highly likely you can get away with a lot less cooling and dehumidification than you thought possible. That said, it’s wise to consult with an IT professional before doing this to ensure you don’t damage your data.

Another innovation that can help you cool down your data center more economically is utilizing an economizer system. This technology uses cool air from the outside to provide “free” cooling cycles for your data center.

Want more tips on reducing your overall IT bill? Curious to learn more about virtualization? Call us today to learn from one of our experts.

This entry was posted in General Articles A, Virtualization – General and tagged data center, energy audit, humidity, it workload,server room, Technology, temperature. Bookmark the permalink. Both comments and trackbacks are currently closed.

Three BI terms explained

In order for a business to get more out of their existing and future data, many are relying on Business Intelligence (BI) solutions. If you are looking into a BI system for your business you will likely come across data related terms that are important to know about. Three of the most commonly asked about are data mining, data warehouse, and data mart.

What is a data warehouse?

The concept of a data warehouse is an interesting one and also a difficult one to define and pin down largely because it can cover such a broad area. The most concise definition we can give is that it is a database that integrates data from many different locations and databases into one consolidated database.

Data warehouses store both current and historical data, and rarely contain unique data. Instead, they aggregate data from other sources in order to make this more accessible. They might store important information from sales, marketing, ERP, customer interactions, and any form of database in order to quickly generate BI related reports.

The name undoubtedly conjures up the idea of a large warehouse-like building storing infinite amounts of data. However, most data warehouses are actually tables which are created by taking data from various sources and cleaning it up so that relevant data is stored in the warehouse in a way that makes it easier to reach when needed.

What is a data mart?

A data mart is a smaller data warehouse that stores data. These are based on a specific area or business function e.g., finance or marketing, etc. In fact, most modern data warehouses are actually made up of a series of smaller data marts.

The key difference between a data mart and a data warehouse is that data marts are usually smaller, focusing on one specific area, while a data warehouse covers the whole organization.

What is data mining?

When talking about Business Intelligence, many experts will refer to data mining. This is the act of analyzing data in order to identify patterns. The data that is mined can then be transformed into useable information. Many companies store this mined data in databases, a data warehouse, or a data mart.

Want to learn more about these terms and how your company can benefit from a BI solution? Contact us today.