The information that is discovered after a session of data analytics can be used in various ways to boost businesses across industries.
Data analytics is a process where large sets of data are examined. The objective is to search for patterns, trends in the market, preferences by customers and previously unknown correlations.
It can be used to optimize marketing, exploit new opportunities for revenue, increase the quality of customer service, improve employee productivity and promote the efficiency of operations. This information can also be used to create competitive advantage over your rivals. Data analytics is normally performed on big data sets.
These data sets are normally stored by remote DBA experts in specially designed databases. Known as NoSQL databases, they are designed such that they are infinitely scalable. This means that they can store exponentially large amounts of data. The databases are hosted in machines that perform parallel processing. There are many different types of NoSQL database software. Examples areMongoDB, HBase, Raven DB and Apache Jena. There is a direct correlation between big data and these types of software. This is because the data is stored in the databases for processing and access.
The database technologies that are required for the purpose of storing big data make it so that the investment is cost effective in the long-run. Technologies such as Hadoop make it affordable to store thousands of terabytes of data. The revenue that a business gets by leveraging big data is much more than the cost of investing in NoSQL database software.
It promotes quicker decision-making in the business
There is a technology that is known as in-memory analytics. It increases the speed of retrieving data from NoSQL database software. By doing this, the information stored in the databases can be presented to decision-makers quicker and result in a faster decision-making process.
The innovation of new products and services
The information that is collected from the big data sets can be used to innovate new products or services. Most of the data is usually about customers and their experiences. As such, with a good understanding of what they want, a business can respond to this need by providing a product that fits the requirement. This can lead to increased revenues and better profit margins.
In-memory data analytics is a process where high-impact data mining is conducted. Special processes and tools are utilized to retrieve relevant data. High computational power is utilized, resulting in fast retrieval. Here are the characteristics of in-memoryanalytics.
In-memory data analytics leverages machine learning to find and retrieve information. Special sectors of memory are set apart for every data retrieval session. As a result, the process retrieves results at lightning-fast speeds.