Refining Crude Data into Startup Fuel

Cloud Data

By refining crude data, you can generate fuel to run your business – with all aspects handled quickly and affordably through the cloud.

  • Crude Oil and Crude Data
  • Centrality of the Cloud for Big Data
  • Four Steps for Data Refinement
  • Strong Machines to Refine Crude Data

Crude Oil and Crude Data

It’s easier to understand big data if you think of it in terms of crude oil. Crude oil has to be refined – distilled to separate the desired hydrocarbons – in order to be useful. Data must be similarly processed, boiled down into the most relevant components that can power your company with insight and innovation.

While data and crude oil do have similarities, one area of major difference is abundance. While there is obviously a finite amount of oil, with prices based on availability, the amount of data that businesses have at their fingertips is absolutely mind-boggling. In fact, that’s become exponentially more true in the last few years.

Between the dawn of humanity and 2003, we collected an aggregate of 5 billion gigabytes of information. If you are familiar with large-scale data projects, that is NOT an impressive figure. In fact, 6 times that amount were produced every hour in 2013.

Centrality of the Cloud for Big Data

Technologist Matt Wood explains that cloud computing is essential to big data – giving the example of the Weather Channel. Prior to the cloud, the TV station gave updates six times a day on a couple million locations. Now it gathers and disperses new information from billions of sites numerous times an hour.

“Enterprises want a platform that graciously allows them to move from one scale to the next and the next,” said Wood. “You just can’t get this if you drop a huge chunk of change on a data center that is frozen in time.”

The problem for a startup is usually not that they don’t have enough data or how to use it when deciding on questions like ‘How Many Shares Should My Startup Authorize when Forming?‘ It’s that they don’t know how to sort it – to filter the data into an organized raw set and refine it so that it’s useful.

In 1901, breakthroughs in oil refining technology that were initiated at the Spindletop dome led to the fossil fuel era. With concerns over smog, water pollution, and climate change, some of us would prefer that the oil era was never realized. Data insights are easier to embrace, offering startup fuel without the immediate environmental impact.

Four Steps for Data Refinement

The question is how to take data and leverage its greatest potential. When you refine with the following four-step plan, you can prepare your information for business:

  1. Document objectives.

It will be unsuccessful to just start rummaging through your data, so establish goals.

“Determine the metrics you want to measure and how they will be monitored and communicated to the team,” says Future Technologies CEO Asha Saxena. “Look critically at the data you find in terms of those metrics and use it to start experimenting.”

  1. Gather ideas and perspectives.

You want to get everyone’s point-of-view on how data could be used effectively by the business.

An easy way to do that is to turn everyone in your company into an amateur data scientist. Give everyone access to cloud-hosted analytic systems so that they can potentially notice interesting data relationships during the course of business.

Another way could be by learning through experts in the field. Not everyone prefers to try the hit and trial method and that is where this approach comes in. Those interested can enroll in relevant courses where they can find their mentors. It is advisable, however, to look at the online reviews of the particular program before enrolling in it. Those unsure what it means can look into sites similar to, for reference.

  1. Look on the inside.

There are many data sources available, but be sure to pay special attention to what you produce yourself – what is immediately available right now.

“Maybe you’re already monitoring how much time people spend on the landing page of your app,” Saxena suggests. “Expand on the pool of data you’re already collecting to gain insights specific to your customer base.”

  1. Zero in on the valuable numbers.

What specific measurements are the most important for you? How can you best benchmark the performance of your staff and how well your customers’ needs are being met?

When explaining the success of Apple, Steve Jobs said, “Focus is about saying no.” To refine, say no to anything that isn’t worth your time.

Starting from an internal set of data, you can branch out. “Once you have a solid foundation of data from internal practices,” says Saxena, “you can explore open data sources, including, UNICEF, the World Health Organization and Google Public Data Explorer.”

What does that look like in practice? The LAPD uses its own information in conjunction with open data systems for a predictive tool that attempts to determine future locations of crime. In the 12 months following the adoption of this tool and the reorganization of officer patrol locations in response to the predictive outcomes, Los Angeles County saw its burglary rate plummet 26%.

Strong Machines to Refine Crude Data

If you want to become a data tycoon, you have to make that black gold usable. In order to refine crude data affordably, it’s essential to have a strong cloud system.

At Superb, our cloud virtual machines are rated via the PassMark benchmarking system – the only practical and objective comparison of actual CPU performance. Our servers usually test 4 times better than machines with similar specs from AWS and SoftLayer. Refine your data now.

By Kent Roberts

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