Huge amounts of data are produced every single day with some estimates going as far as asserting that the sheer volume of data doubles almost every year. Thanks to this exponential growth it is becoming all the more difficult to extract any useful information regardless of how critical it may be.
This information is usually stored in a ‘data warehouse.’ This is basically a repository for all sorts of data that may have been gathered and eventually culled from many different sources, which may include succinctly summarized information taken from internal systems, various corporate databases, as well as data from external sources.
The subsequent analysis of all these huge amounts of data includes different techniques that may be utilized for the same, such as statistical analysis, simple query and reporting protocols and even more otherwise highly complex multidimensional analysis methods including data mining operations.
In today’s increasingly fast paced environment, a lot of companies and other organizations are spending far too many precious resources collecting, managing and collating raw data. This in turn means they have far less time to actually analyze the same and thereby derive tangible value from it.
Currently, there is a greater need for any business concern to react quickly to the demands of their business by both understanding customer needs and demands and responding to the same as soon as possible.
The ‘data explosion’ of all forms of both structured and unstructured data originating from within as well as outside the business enterprise has turned an extremely competitive landscape even more competitive. Add compliance and regulatory pressures to the equation and it would become clear that without such in-depth and detailed analysis many businesses will fall far behind their competitors in the field.
Big data analysis is roughly analogous to most forms of conventional analytics as well as business intelligence solutions. This is because big data mining and subsequently analysis of the data mined is instrumental in uncovering and showcasing many otherwise hidden patterns along with their correlations, and any other highly useful business information that may be periodically gleaned though the perusal of such data.
Broadly defined, data that is considered high velocity, high variety and high volume in size and configuration may be considered ‘big data’ and as such this is a prized information asset. However, extracting valuable information from it requires mining efforts that are not just highly cost-effective, but also innovative as well, so that all the huge amounts of information that is mined and processed can offer better insight and significantly enhance the overall decision making process. The three key aspects of big data include the following:
Here ‘volume’ refers to the actual amount of information or data available. This may include both machine generated as well as sensor derived information, different networks, social media etc. Since IT infrastructure is getting better by the day (both physically and though cloud based networks) far larger amounts of data are being stored than ever before, thereby increasing the need for comprehensive data mining operations.
Variety basically denotes the different types of data available and it may go well beyond the usual dates, digits and strings of information and include highly unstructured data such as click streams, video, text, audio and multimedia files. In a nut shell, the more the sources, the greater the amount of data generated
This is the speed with which data is processed. The faster the online connection the faster data is generated and downloaded. Rapid frequency stock trading for instance or machine-to-machine processing are very fast paced means of data generation.
There are huge benefits of big data analysis and they cover a cross section of categories that include the following
Many well-known and established Big data tools such as Hadoop for instance, help companies to store huge volumes of data at far lesser rates than saving the same in a more traditional, physical database setup.
We ensure that any organization desirous of utilizing any large scale big data tools may use our single or multiple Hadoop clusters to increase the capacity of their data warehousing space The data can easily be moved from the traditional database to our Hadoop clusters so there is no need to expand the physical capacity of your infrastructure. The ease of movement ensures there is no need for further expansion of your own database since all information can flow from the database to the Hadoop cluster and vice versa for all processing and mining needs. This way infrastructure related costs need not rise and can be kept to a minimum.
For any business to remain successful in the long term they need to retain their ‘edge’ or sustainable competitive advantage to remain ahead of their competition for extended periods of time. They can do this by utilizing our big data mining and analysis related tools to increase their customer retention as well as help develop new products that resonate with market trends and dynamics. We can help them extract the required information with which they can augment their decision-making abilities and thereby determine their strategies to always remain ahead in their game.
One of the greatest benefits of using our big data mining and analysis tools is the strong possibility of discovering ever newer and more exciting business opportunities in previously unexplored niches.
We offer both up and up and coming entrepreneurs as well as established businesses many advantages of using our mining services in both advertisement and marketing technologies. Apart from that it is also possible to devise new methods of value addition for the end consumer so that not only are his expectations met, but he is out rightly delighted. Other than that, it is also possible to discover an all new customer segment as well and thereby add value to your overall business model.