data analysis

Data is Meaningless Without Analysis

Data is Meaningless Without Analysis 150 150 Kerry Butters

There’s value in organisations being able to analyse social media information and compile profiles to better target their customers. But creating, documenting, and retrieving vast amounts of data is one thing. Understanding it is an entirely different matter.

Context is Key

Measuring ‘likes’ or searching for keywords and phrases is pretty straightforward – a “sentiment analysis”. You might be tempted to develop a marketing strategy directly derived from this.

But there’ll always be examples of impulse buys, or snap decisions in the heat of the moment. And data samples may include information that’s not so easy to quantify – like pictures or videos.

In fact, the majority of actions will be based on the context surrounding them. Brand A might cost less, but B offers greater satisfaction. The sports car looks great, but what about the kids? And so on.

If a data analysis tool can’t provide further context around the solutions it offers, it’s at best, an expensive waste of time.

Informed Decision-Making

Investments in data analytics can be useless – even harmful – unless employees can incorporate that data into complex decisions. Meeting this challenge requires an understanding of human behaviour which is often lacking – and not only in IT departments.

Operational Intelligence

On a par with business intelligence is the need for operational intelligence. The ability to see and know everything that’s happening in your IT environment, at any moment. A tall order, considering the levels of scale and complexity, involved.

But armed with this knowledge, IT teams can better collaborate, fix problems, and provide support for product launches, application rollouts, migrations, upgrades, and other initiatives.

Operational intelligence may be obtained from four primary data sources:

1.  Machine data: such as log files, SNMP and WMI. Data from sensors (e.g. on wearable devices) also applies.

2.  Code-level instrumentation: which traditional application performance management (APM) is based on.

3.  Service checks: which provide insights on whether applications are up or down, and how well they’re performing.

4.  Wire data: the data-in-motion, describing all communications between systems.

Of these, wire data has the greatest potential for transforming intelligence.

Get Wired!

Wire data is the record of everything that’s happening in IT, in real time. It provides an in-depth view into the performance, availability, and security of your environment – including issues you might otherwise be unaware of.

Wire data is unstructured, and also high-velocity; generally at 10Gbps in data centres, and faster still in cloud environments. Powerful packet processing capabilities are required, just to keep up.

But, with the right tools in place, it can assist with:

1. Detecting Application and Infrastructure Performance Issues: Based on communications over the wire.

2. Big Data Analysis: You can extract specific pieces of wire data and feed it into analysis platforms such as MongoDB or Splunk.

3. Spotting Data Theft: You can easily identify when data is being stolen from your back-end databases – a particularly vulnerable place. Using wire data, you can spot when queries are being made by unknown or untrusted sources.

4. Parsing Data: Using Big Data analysis tools, you can mine that data for business intelligence purposes. 

5. Generating Meaningful Reports: Which will enable you to analyse what’s happening, with the data you collect.


Visualisation helps put data into context and bring business cases to life, through the creation of visual models that represent what’s happening to and with your data.

Most people are now moving toward the kinds of models having dashboards of information where you can zoom in or out. These help to understand what happened or did not happen based on actions you took – a hindsight analysis.

To look into the future, visualisation models need to be more dynamic. 

In the Real World…

Let’s take utilities (power, gas supply etc.) as an example. Most have archaic records and inaccurate information, with no idea where all of their underground assets are located. That makes it hard for them to deal with service interruptions that can occur when a power line is accidentally cut, or a water main bursts.

In the USA, the Las Vegas city government has taken advantage of smart data to develop a living model of its utilities network. VTN Consulting helped the city aggregate data from various sources into a single real-time 3D model using Autodesk technology. The model is being used to visualise the location and performance of critical assets above and below ground.

Companies in the health sector are reporting impressive results as they use Big Data analytics to increase efficiency, improve patient outcomes and provide greater personal care. These are largely fuelled by the US government’s push for more meaningful use of electronic health record (EHR) systems.

How to Make Data Meaningful?

Work backwards, and ask a few fundamental questions:

·   What business processes or decisions do you want to improve? (Make sure to get management involved at this level.)

·   How will these decisions improve the business?

·   What are you trying to maximise?

·   What are the most meaningful elements used to measure progress toward those goals?

·   What types of analysis do you need to perform to expose the data, explore “what if” scenarios and work through alternatives to optimise your operations?

·   What types of data do you need to collect in order to feed the above analysis and decision-making?

Is Big Data Essential For Business?

Is Big Data Essential For Business? 150 150 Kerry Butters
 Image by  Domo

Image by Domo

Data is more a part of our lives now than it has ever been. It’s woven into every sector of the global economy and the harnessing of that data by businesses and individual alike is becoming the norm.

Big Data is what we get when the data sets collected become too large and complex to analyse using standard methods. This data comes from all sorts of sources, including web browsers, social media and consumer information. By sifting through all of this information business managers are able to make much more informed decisions and therefore move their company forward with confidence.

The Benefits of Big Data

Future ready – The internet of things is a hot topic in 2014. As products begin to broadcast data to one another to improve their efficiency. The amount of data available to manufacturers and suppliers is going to grow even greater as a result. Investing in an infrastructure that can handle and analyse Big Data now will put your business in an excellent position for the future, even if you’re not concerned with the internet of things, Big Data is listed by Gartner as one of the technology trends you can’t afford to ignore.

Customer Insights – Near the top of a good business’s objectives is to react and respond to the needs and desires of its customers and clients. Big Data allows your business to make accurate predictions about the near-future needs of those who use your business regularly, and the business of your competitors. This can give you the edge that you need to both excel in your chosen field and compete with other businesses.

New Business Models – Some industries have seen Big Data create completely new business models. Algorithmic trading allows businesses to analyse tremendous amounts of market data every minute, providing them with information on where the real opportunities are. This kind of speed would have been unheard of a decade ago. Retail companies are using Big Data to change their purchasing behaviours, making purchases based on fact rather than speculation.

Better In-House Operations – Big Data may be the final link for companies looking to achieve maximum operational efficiency. By constantly assessing the efficiency of their workers and work processes, managers will be able to highlight the points where they’re losing money. Insurance companies are already speculating how they can use Big Data analytics to speed the processing of claims and spot potentially fraudulent claims that need investigating.

Improved Sustainability – The Guardian recently reported that Big Data could see businesses able to take much greater steps towards becoming sustainable and nature friendly by using the same information that improves their in-house operations.

Harness Your Staff’s Potential – Data analysis doesn’t have to stop at your customers, businesses who turn their analysis inwards and review their own staff have reaped the benefits too. By analysing the work patterns and talents of their employees, managers can make sure that staff with niche skill-sets aren’t going to waste and introduce multi-discipline roles to improve efficiency.

The challenges of Big Data

Security – Obviously if you’re handling tremendous amounts of customer and client information then you need to be absolutely sure that that information is well protected from any hostile forces that might want to misuse this information. If you’re going to invest in Big Data we advise you also invest in beefing up your security. Fortunately, Big Data security is set to be one of the big talking points of 2014, so there will be plenty of opportunities to make improvements across the board.

Accumulation – Data doesn’t just turn up on your desk, you have to invest in accumulation systems to help you collate all the information that’s out there and turn it into useful, business-driving data. These can be expensive, but they are an important part of any business’s Big Data strategy.

Analysis – Big Data needs high performance analysis because there’s just so much of it. Datamation wrote an article last year about the amount of data we create every minute, and the numbers are staggering. According to their data in June, the human race wrote over 204 million emails a minute, queries Google 2 million times, watched 48 hours worth of YouTube Videos and produce over 100,000 tweets every minute. That’s a huge amount of information to process and eke useful data from, but it’s almost certainly worth it.

Datamation also noted that over $272.000 was spent on e-commerce every minute. Like the other numbers it’s likely to have gone up in 2014 to even more. People are spending more money online because it’s often cheaper, more convenient, and more varied. It also means more data, and that data is becoming more and more accessible every year. For a business, passing on all that information is passing on a huge percentage of potential new customers for your business once you isolate their desires using Big Data.

It’s Time for Big Data

Big Data analytics is looming over the business sector like never before. 2014 is the year where we’ll see businesses really kick their analysis into gear. The target for many will be to become capable of real-time analysis of data as it’s collected, and then react to that information accordingly. Any big company unable to do similar may find themselves falling behind, and any SME’s getting into Big Data early could well see themselves rocketing to the front of the pack.