• Data volume: When data volume is thought of the very first issue that occurs in storage. As data volume increases so the amount of space required to store data efficiently also increases. Not only that the huge volumes of data need to be retrieved at a fast speed to extract results from them. Networking, bandwidth, cost of storing like in-house versus cloud storing are other areas to be looked after. On
Big Data Training
With the increase in the volume of data, the value of data records tends to decrease in proportion to age, type, richness, and quality. The advent of social networking sites has led to the production of data on the order of terabytes every day. Such volumes of data are difficult to be handled using existing traditional databases.
• Data velocity: Computer systems are creating more and more data, both operational and analytical at increasing speeds and the number of consumers of that data are growing. People want all of the data and they want it as soon as possible leading to what is trending as high-velocity data. High-velocity data can mean millions of rows of data per second. More Info On
Big Data Certification
Traditional database systems are not capable enough of performing analytics on such volumes of data and that is constantly in motion. Data generated by both devices and actions of human beings like log files, website clickstream data like in E-commerce, twitter feeds can’t be collected because the state of the art technology can’t handle that data
.• Data variety: Big data comes in many a form like messages, updates, and images in social media sites, GPS signals from sensors and cell phones and a whole lot more. Many of these sources of big data are virtually new or rather as old as the networking sites themselves, like the information from social networks, Facebook, launched in 2004 and Twitter in 2006. Smartphones and other mobiles devices can be bracketed in the same category.
As these devices are ubiquitous the traditional databases that store most corporate information until recently been found to be ill-suited to these data. Much of these data are unstructured and unwieldy and noisy which requires a rigorous technique for decision making based on the data. Better algorithms to analyze them are an issue too
• Data value: Data are stored by different organizations to gain insights from them and use them for analytics for business intelligence. This storing produces a gap between business leaders and IT professionals. The business leaders are concerned with adding value to their business and obtaining profits from it. More the data more are the insights. This, however, doesn’t go well with the IT professionals as they have to deal with the technicalities related to storing and processing the huge amounts of data Get More Information On Big Data Hadoop Training