Data analysis is the key to determining the success of large data

In recent years, I've been working with executives at big data companies to find out how to solve their problems. Some interesting questions persist. It is clear that we are still in the early stages of understanding certain issues, and we may still have a long way to go to fully understand and use effective solutions to these problems.

Companies such as Facebook and Google are getting a lot of information. They are generally subject to complaints of privacy violations, although we do not know that these companies use the data they collect to calculate what information is available about us. We always assume that they use these data information to our disadvantage, even if they are likely to try to use this information for our profit.

No better way to protect your data

Historically, many of the issues surrounding large data repositories involve managing them. This is primarily about ensuring the scope of the people who need access to this data: from management reporting to compliance with all management rules, so that they can get the information they need when they need access to the data. This also means that you must ensure the security of your data store. This has historically become the supplier of iron-hardened service standards.

These historically managed data means that we have been treating these data like pirates ' treasures, just trying to find creative, inexpensive ways to bury them. But did not come up with the same creative plan to analyze and get them in time.

We can be sure that the treasure is there, but we don't know where it really is. Even some of the data is really old, and its indexing and storage is so bad that we sometimes think it would be better if we didn't store it first.

Emerging public cloud resources promise low-cost storage with future high probability of access. Any data information treasure resources are rows of neatly stored. The only trade-off is, of course, security, management and compliance issues.

As data continues to grow and corporate IT budgets are compressed, the trade-offs of these factors seem to be out of the question. That is, until the offender finds and publishes the data, it poses a risk. Our business even has a risk manager position, but the position is slowly becoming less meaningful to protect corporate assets as the financial markets collapse.

Data analysis is the way to determine the success or failure of large data.

Now, we realize that the key is not the big data itself. In contrast, data and mobile device access analysis and Results report. Executives are increasingly discovering that if they can get real information from the data they collect, they can make better decisions, avoid painful repetition errors, and improve their position in the business and the industry as a whole.

Knowledge, it turns out, is power. So today's successful people are starting to focus more on their customers, their partners, their employees and their business environment than their competitors.

Enterprise executives in the new era use tools for more robust data synchronization. This ensures the accuracy and timeliness of the data being analyzed. They offer mobile clients that can display results on smartphones and tablets. They use cloud services to address both the cost and security requirements of the enterprise.

Hadoop has become the largest data analysis platform in which vendors are using Hadoop to compete for the best tools. However, as vendors begin to spend more time developing accessories than optimizing the entire solution, or when choosing partners with no intention of creating bottlenecks, these optimizations may short.

Choose your enterprise's data analysis solution wisely

Finally, when I heard President Obama's re-election of the CIO analysis concluded that the big data itself is not important parts. It is important to provide your managers with the answers they need.

This may sound simple, but it does require that the vendor must meet the following conditions:

· Have a lot of experience in your business and industry.

· Willing to take on the whole solution.

· Have a good record of meeting your business expectations.

· Experience with both public and private cloud resources.

· Ability to handle traditional data storage and real-time data streams.

In short, this is not a do-it-yourself problem. You need experienced, reputable, reliable and trustworthy suppliers. Only a few vendors meet these criteria. You need to make an informed choice.

The writer Rob Endler is the president and chief analyst of the Enderle Group. He has previously served as a senior researcher at Forrester Research and Giga Information Group. Prior to this, he worked for IBM as an internal audit, market competition analysis, marketing, finance and security management and other related positions. Enderle currently writes about new technologies, security, and Linux-related columns for various publications and is invited to participate in national news television recordings, including CNBC, FOX, Bloomberg and NPR.

(Responsible editor: Fumingli)