Big Data Analytics is fast growing as a good practice in a lot of domains of late: so we may have a stage where these firms who are toying with it say that it is no more a secret some day in near future. The end result of this flourishing of big data now begins to play out that secrets whether big or small with respect to organisations have no real future. There was a time when decisions were more emotional but that will probably not be the case with unraveling of the secret of big data analytics.
With the usage of big data analytics techniques the detection of frauds and buying patterns of consumers can better be understood and action suitably taken. All this has become possible due to the data-intensive science involved in big data analytics.
In fact the presence of data is creating a new competitive edge which we may classify to be for 3 major reasons namely business, technology & finance. In the business realms through the presence of data new innovative business models can be created along with new insights to give a competitive edge. In the technology side we see that data and the storage requirements for it have grown exponentially and data is also available everywhere meaning the traditional solutions are not keeping pace with it which means the data handling capability needs an overhaul. In the finance area data can be advantageous to provide those sources that are bulging the costs and those hard ware and software that are required to handle it.
So from the above points it indirectly becomes evident to represent Big data through a formulae that big data is a summation of transactions, observations & Interactions.
We currently exist in an era where 3 periods make up digital data; they are the social era, information & the big data eras. The fiery growth of data comes from various corners like mobile & smart devices, business transactions conducted either online or through hand held devices, sensors like RFIDs, social & traditional media, High density video, Web-clicks, Ad words, cloud computing, stock & share markets, etc. All these data that are generated in the due course of interaction happening between machines, people, apps and combinations of all these. Those who are or have been ignoring it shall now have to pay importance to it in this era and apply big data analytics to it. This visualization of the data that is being networked and its components at once validates what is going around us in the world, in all sectors of the economy, society and science, and also in a combination of these.
Everything around you is information
Organizations today exist with a big thanks to information available around it and this combined with science has made it that ultimately everything is now based on information. Data forms the basic fundamental aspects & foundation for this information we are working and with more relevant facts there better diverse issues that are better understood and with this one can anticipate better decision making. As a result of this there is this correct decision making in this highly competitive age and crisis around businesses. So the presence of big data is ultimately proving to be a blessing in disguise at this age where crisis is common and decision making is critical. After all big data analytics is here to stay to fully comprehend and predict situations that are to happen in future. This argument is definitely a strong one and with the evolution and availability of soft wares, hardware, algorithms and apps analysis of data has now become genuinely more accomplishable for better decision making and planning.
Another area in which we might require a complete dataset for analysis is in fraud detection. Here the signals are so small that it sometimes becomes impossible to work with random samples until these signals have been identified appropriately. Based on that, all these data need to be analysed in this field area as well.
Here what we are doing is checking for the possibility of data collusion using big data analytics to examine if the illegal collaboration that has been directed to impede others with intent of sabotaging them just like the casino’s world. In fact we can have applications to churn and fraud detection needs as examples for big data analytics usage.
Some of the big data managing challenges: are these your headaches?
• How do I better manage both my unstructured and structured data
• Which data and from which source is it more useful in your strategic planning
• Do you have an idea of how complex your data is and how I plan to manage it in future?
• How fast or what is the frequency of data processing intended and what issue are you planning to solve with those data?
• What is your budget set for managing these data?
• What security measures are in place to handle and secure data?
• Are the current resources available in house capable of handling these data?
Based on the above challenges we can confidently jump on embarking on a big data project if:
• The firm has the right mind set and culture at its disposal with which the start and end points can be clearly marked.
• There is full support from the top level management on this initiative
• The needed expertise and experience are in place along with the framework and tools to execute
• There has been sufficient budget allocation for training, adoption of culture in house
• If the right partners are also in place.
So with the warning that Big Data Analytics is not merely a technology toy but an integral part of strategy, marketing, or R&D may already be familiar through this. Also it becomes evident that those stages when we pursue to create “magic moments becomes a reality if we abandon the conventional thinking & patterns and work on getting the structured unstructured data to better reflect to gain better results overall.