We are living in the era of information surplus where information and data is omniscient and omnipresent. Our lives have become digitized today. We are generating and managing volume of data of various variety – streaming data, mobile data, social media content, day to day communications, banking transactions, weather logs, etc. Making sense of these available data has become imperative. In this context, Big Data analysis has become the talk of town. People mostly talks about Big Data Analysis at different levels of abstraction and understanding. They talk about real time and advanced analytics, frameworks and products, which is typically not a good idea. So let’s try to step back and look at what Big Data means?
Big Data is described by three characteristics of data: volume, variety and velocity. Volume means making sense from terabytes—even petabytes—of data. Variety refers to diverse set of data being created from sources like social networking feeds, videos and audio files, emails, sensor data and other raw data. Velocity means bringing up data from real time data sources like websites, ATMs, point-of-sale devices, and other sources. Thus, Big Data analysis can be define as the process of analyzing large volume, variety and velocity of data to discover buried patterns, hidden correlation and other useful information.
Now the next question that comes to our mind is, how Big Data creates value for my business? Big Data enable business value in four broad ways. First, it helps making data more apparent and workable for business. Second, it enables better decision making through richer and broader data sets. Third, it helps to do narrower segmentation of customer for targeted marketing campaigns and sales pitch. Finally, opens new business opportunities by developing new and innovative products and services.
Business that have begun to embrace Big Data approaches are now realizing that the possibilities for new innovation, improved agility, optimizing productivity and increased profitability are nearly endless. There are several use cases associate with the Big Data.
Let us take an example how supply chain process can be optimized using Big Data. In supply chain system, enormous amount of data is collected from a variety of sources ranging from ERP systems, supplier’s details of order and shipment, web log files of customer shopping patterns, sensors data like RFID, electronic meter readings, data generated from mobile devices data and social channels, etc. Big Data in real time can help supply chain process for example by tracking minute by minute shipment details, thus providing deep visibility and control on the process, By tapping data from real time web logs and social channels, industry can predict market trends and shift to a demand–driven production model. This can help them to tune their production schedule, procurement plan, distribution plan, pricing model and much more.
Let us take another example of how Big Data can create real impact. The telecom industry is already generating large volumes of data including call detail records (CDR), network data, customer data from calls and purchases to downloads and updates. The data volume is so high that manual analysis is unmanageable and impossible. This is because legacy software systems cannot handle this data load, resulting in valuable data being ignored and untapped. The telecom industry with the help of Big Data can store and analyze these data patterns and usage. Combined with the customer demographic data, industry can get a good idea of what is important to their customers and become more responsive in product offerings and marketing initiatives. Big Data analysis can also help in predicating customer churn by identifying the customers that are most at risk of leaving, and tailor special offers or programs to retain them. By examining the user behavior, they can offer personalized recommendations for services and add-ons. Also using real time network information including call duration, answer/seizure ratio and post-dial delay, the network administrator can quickly see issues as they arise and proactively take corrective actions to resolve them even before customers start complaining about the same.
Now you can imagine, Big Data is different from traditional relational database systems as it entails more advance mechanism to understand, process, store and analyze data. Big Data ecosystem constitutes of data storage and management, Big Data analytics tools and technologies, and associated IT services. To develop and manage this, Big Data requires two kinds of skillset – First, the technical skills that are required to store, process, discover and analyze the massive and data sets and the knowledge of Big Data architectures (i.e.Hadoop, MapReduce, Hive , Key Value stores etc.). And second – the next-generation business analyst with strong statistical skills who are able to extract information from large data sets and then present it to businesses that should be understandable and valuable. But in current scenario, there is still a significant shortage of skilled professionals who can evaluate business needs and impact, and apply the Big Data concepts and technology/tools to it. This poses biggest impediment to adoption. There are many other important issues like data security, policies and governance, organizational change and talent, industry structure considerations that will have to be addressed in order to adopt and realize the full potential of Big Data.
To overcome the aforesaid issues, enterprise can take help from technology vendors that can help with strategy, consulting, training, technical and professional services. A right technology vendor can help in identifying and prioritizing the most valuable Big Data opportunities for their customers – the ones that will generate the highest ROI using Big Data and will create the most effective roadmap, architecture and plan.
You can imagine all the possibilities that Big Data can bring to your business, but you should find answers to few important questions.
Do you envision that Big Data can create new opportunities for your business in areas such as Product/service development, design, marketing, sale and support? What are the possible Big Data use cases for your business? Can your current environment handle it? What are the organizational readiness and areas that require investment?
This article was published in DATAQUEST.
