It was never easy to deal with data in the past and with all new data streaming all around; companies are struggling with the same. Starting from production line sensors to smartphones, every single thing is generating data. Apache Hadoop has become the most popular choice for storing and managing big data worldwide and it comes with serious competitive advantages in terms of risk management, operational intelligence and various such things. Let’s look at each of these in details:
Security breaches and fraud have become very common these days and the latest sophisticated security solutions are failing to prevent these and the companies are facing great challenges in protecting their big data. Big Data Hadoop on the other hand can offer excellent security solutions and help enterprises to analyze huge amounts and different kinds of data in real time. It also speeds up the threat analysis process and improves the ability of accessing risk by making use of machine learning models that are highly sophisticated.
Some of the features offered by Hadoop big data as far as security and risk management is concerned big data include security information, application log monitoring, event management, fraud detection, network intrusion detection and risk modeling.
All companies need ensure that their productivity and profitability is maximized and this is required in order to stay in the competition. Many a times, it has been seem that a subtle change in the environment makes way for great profits and improvement even after analyzing and optimizing the operations. You optimize the requirements of your organization by taking granular measurements from the sensors and by tracking patterns. Hadoop distributions like MapR etc. are supported by Cisco that provides analytics and infrastructure and such joint solution offers you the ability to evaluate data as per the speed demanded by your business.
Specific use cases in this include quality assurance in the assembly line, supply chain and logistics, exploration and production optimization, preventive maintenance, smart meter analysis and the likes in the big data platform.
The number of social media channels is increasing day by day and dealing with data coming from these sources is becoming difficult for the organizations. Big Data software can be used to integrate and analyze all these data in a cost-effective manner and to gain customer insights and build long term customer relationships in order to maximize revenues.
Specific use cases, in this case, include advertising optimization, clickstream analysis, social media analysis, and many more.
Big Data solutions can also be used as an EDH in order to transform, store, filter, clean, analyze, and also gain new value for different kinds of data. In order to build a successful EDH, you need to start with selecting the right technologies in three main areas viz. data processing platform, infrastructure and foundation system to drive EDH applications.
Data refining, the collection of raw data in Data Lake, data warehouse optimization are its specific use cases.
Go through Big Data Hadoop tutorial for more details and other big data services.