Technically Speaking

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5 Things You Need to Consider Before Delving Into Big Data

The benefits of big data to a single organization can be profound. When used correctly, it can provide huge savings, help a company reach more customers, improve customer satisfaction ratings, boost production levels, assist in developing better products, and improve business intelligence. But there are some considerations to make before delving in head first. Here are five things to consider before taking on big data initiatives.

1. Big Data is Messy and Time-Consuming

Taking on big data is a bit like having kids. You have to tolerate lots of messes to get the benefits.

Big data is a big mess. Unlike the data kept in neat and orderly spreadsheets, big data is unstructured and can consume as much as 80 percent of a data scientist’s time to clean up and prepare for analysis. This means that big data initiatives are time-consuming and costly before yielding a measurable benefit to the company that invests in it. In order to realize the potential of this investment, you have to commit to the long and tedious process, and to be patient until the rewards become evident.

2. Big Data is Only as Good as the Humans Analyzing It

Like most technologies, big data is only as good as the people managing it.

In itself, big data is useless. It has no value until humans process it, analyze it, and find ways to use what it says. It’s hard to find experienced professionals to work the big data for you, and even harder to undertake such an initiative in-house without outside help. There are a number of consultants and vendors offering big data solutions, but it’s important to find the right one to help you with your particular needs.

3. Big Data is Best Served With Lots of Variety

Big data only becomes valuable when there is lots of it, and when that data comes from a variety of sources. For example, your internal data (even if it is many petabytes) isn’t as valuable as a combination of internal and external data. Big data’s value only reveals itself when layer upon layer of data is assembled in order to provide an accurate picture of reality. This often means finding additional sources of data from outside your organization.

4. The Tools for Managing Big Data are Complicated

The primary tool for analyzing big data is Hadoop. While Hadoop’s usability has come a long way recently, it’s still quite an undertaking to master. You’ll also need to plan for the infrastructure to house and process the data, which can be done either internally with an onsite data warehouse, or externally using a cloud-based data warehouse. Even with onsite data warehousing, you might still opt for a cloud-based backup of your data. Data security is also a prime concern, as large collections of data analysis are valuable and subject to attack.

5. Big Data’s Uses are Worth the Difficulties

If it sounds like big data isn’t worth the big hassle, that’s not the case at all! Big data initiatives are slow to get rolling, but yield tremendous benefits. Depending on the industry you are in and the plans you have for big data, there are consultants and vendors offering a variety of big data solutions.

When it comes to big data analysis, processing power and speed is everything. For a 500 percent performance improvement over the virtualized public cloud, visit Bigstep to see what the Full Metal Cloud can do for your big data goals.

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