In recent years, the value of raw data has grown tremendously. Traditionally, that data has been stored on private servers and storage systems. However, the sheer amount of data and the ways that it must be accessed by some businesses has outgrown traditional database systems. This new breed of data is known as big data, and big data archiving is becoming the number one problem of many companies.
Defining Big Data
Many businesses are still in denial about their data stores qualifying as big data. Surveys show that even relatively small businesses in many sectors have more data in storage than the U.S. Library of Congress, which claims 235 terabytes. Additionally, the total data of many companies is growing at a rate of 40 percent per year.
Big data is not all about size. Officially, big data is defined through a combination of measurements that include volume, complexity, permutations, interconnectivity of individual records and the velocity of incoming data versus the speed at which the data is processed.
Because big data is much more than volume, many businesses are beginning to experience problems with archiving and accessing data even when the total volume seems to be within manageable limits.
Big Data Uses
Businesses do not acquire and store big data for no reason. Most businesses have a use for their data. While technology has sufficiently developed to store large amounts of data, the technology required to access and analyze that data is lagging. Many businesses lack the capacity to use their data for the reasons they are keeping it in the first place. Some of the common uses of big data include the following:
• Analyze business transactions
• Calculate investment risk
• Mine customer information for strategy development
• Generate marketing products
• Detect fraud
• Identify system failures
Big Data Challenges
When businesses acquire big data, several challenges are presented. The biggest of these challenges are as follows:
• Processing large and varied volumes of data
• Choosing data worth storing
• Choosing data worth analyzing
The two primary choices available to businesses both have their advantages and disadvantages, but implementing either one takes time and technology that many businesses do not have. The first choice is analyzing massive volumes of data in an effort to be complete. The second choice is determining the relevancy of data beforehand and categorizing it as it is acquired.
Cloud Computing to the Rescue
Several recent technological advancements have made it easier to deal with big data. Following are some of the most important of these technologies:
• Large storage systems and fast processors
• Large-memory systems
• Parallel processing and clustering
Although these technologies may be helpful, they require resources to operate. To make the handling of big data practical and affordable, many businesses are turning to databases in the cloud. International Data Corporation (IDC) predicts that corporate spending on cloud storage systems will be approximately $22.6 billion in 2015.
Big data archiving through the cloud has several advantages for businesses of all sizes . Cloud database services allow businesses to take advantage of state-of-the-art technology that would otherwise be unaffordable, and these services reduce internal IT costs. In addition, cloud services are easily scalable, and they are often packaged with the latest security measures. The savings in time and money provided by pushing big data to the cloud ultimately translates into increased productivity and improved operations.