Big Data Analysis & MIS
Big Data analytics is the examining of large unstructured data sets containing a variety of data types.
Types of Big Data
Now that we are on track with what is big data, let’s have a look at the types of big data:
Structured
Unstructured
Semi-structured
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Characteristics of Big Data
Variety
Velocity
Volume
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Applications Of Big Data Analysis
Healthcare
Big Data has already started to create a huge difference in the healthcare sector. With the help of predictive analytics, medical professionals and HCPs are now able to provide personalized healthcare services to individual patients.
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Academia
Big Data is also helping enhance education today. Education is no more limited to the physical bounds of the classroom – there are numerous online educational courses to learn from. Academic institutions are investing in digital courses powered by Big Data technologies to aid the all-round development of budding learners.
Banking
The banking sector relies on Big Data for fraud detection. Big Data tools can efficiently detect fraudulent acts in real-time such as misuse of credit/debit cards, archival of inspection tracks, faulty alteration in customer stats, etc.
Manufacturing
According to TCS Global Trend Study, the most significant benefit of Big Data in manufacturing is improving the supply strategies and product quality.
IT
One of the largest users of Big Data, IT companies around the world are using Big Data to optimize their functioning, enhance employee productivity, and minimize risks in business operations.
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Big Data And MIS Technologies
While the traditional SQL can be effectively used to handle large amount of structured data, we need NoSQL (Not Only SQL) to handle unstructured data. NoSQL databases store unstructured data with no particular schema. Each row can have its own set of column values. NoSQL gives better performance in storing massive amount of data. There are many open-source NoSQL DBs available to analyse big Data.
It is a Big Data solution from Microsoft powered by Apache Hadoop which is available as a service in the cloud. HDInsight uses Windows Azure Blob storage as the default file system. This also provides high availability with low cost.
This works on top of SQL Server 2012 Parallel Data Warehouse (PDW) and is used to access data stored in PDW. PDW is a datawarhousing appliance built for processing any volume of relational data and provides an integration with Hadoop allowing us to access non-relational data as well.