More and more companies and experts are give preference to Little Data; small amounts of data, limited to a specific person, a specific company or a specific device. We talked about Big Data via various articles and guides. This is practically an introductory article on Little Data.
Little Data Instead of Big Data?
There is opinion that the personal productivity can be increased quickly. Others believe that Little Data provide the same results as large amounts of data or rather Big Data, but to a lesser extent (or it is targeted).Both points of view can be taken into account, the fact is that small amounts of data are part of large amounts of data, they are not exactly the opposite. This means that the principles for the intelligent, efficient handling of large amounts of data – automation, clear business goals and the inseparable aspects of data protection and security – are also applicable for Little Data. In fact, many people and businesses already collect small amounts of data. However, it raises the question of whether and why they should do that.Advertisement
Network and Data Analysis Are Part of Little Data
The data that we need to monitor for performance and productivity, in most cases are already available. Suppose you are engaged in sales and want to determine how efficiently your work is gong. As with the strategy for large amounts of data you would have a hypothesis and determine later whether the data analysis takes this analysis – supporting or is against. In contrast to Big Data, this information is easily accessible. Many companies used a network analysis tools that can monitor the network traffic or the VoIP traffic and tracked the performance of the transmission links, for example.
These platforms for small amounts of data are embedded in the overall average corporate IT setup. If you want to track the time with the highest likelihood of delays, a Network Traffic Analyzer can determine which apps you use at different times of the day. The information is therefore available. It is simply a question of how and why you analyze this information.