Big Data And Predictive Analytics: An Overview
Posted By Saurabh Tiwary | 18-Mar-2016
Over the past few years, we have come across two most evolving terms in the field of technology, viz. Big Data and Predictive Analytics. As there are millions of pages that are being uploaded on the internet every day, it has been the need of ours to organize, filter and make appropriate use of a large amount of irrelevant data that exists on the web.
Data, once shared on the web, in many cases, might not be serviceable for long. Even search engines prioritise and display results depending on the freshness of the material. So, it becomes quite necessary to put one’s thinking on “Are there any means to make use of such trivial data”? The answer is Yes. Since the notion of Big Data and Predictive Analytics are put forward, so many doors have opened towards making most out of the heap of the data.
What is Big Data?
Big data is a term used to describe the tremendous volume of data, be it structured or unstructured that can be used to extract useful data or statistics. Big data can be analyzed for insights of the vast amount of data from any company or organisation that can be useful to make better decisions and strategic business moves.
There are three defining properties of Big Data termed as 3Vs.
1. Data Volume- The Volume of the whole data
2. Data Variety- Various types of data constituting Big Data
3. Data Velocity- Velocity at which data processing occurs
Because of the fact that big data consumes huge time and costs a lot to load into a traditional relational database to check insights, a number of approaches are made to storing and analyzing data that rely loosely on data schema and data quality. As an alternative to this, raw data with additional metadata is parsed. It is utilised in machine learning and artificial intelligence programs use complex algorithms to look for repeated patterns. Big data analytics involves cloud computing and other data storage resources located remotely as frameworks like Hadoop that are deployed to process Big Data often require storage of large data sets. These data sets are distributed across the different cluster and MapReduce to manage; combine and process data available from multiple sources.
How Is Hadoop Related To Big Data?
Big Data and Hadoop are the two most confused-together terms. Hadoop is one of the tools that is mostly used and primarily designed to handle big data. It works to interpret or analyze the results of big data searches by means of specific proprietary algorithms. Hadoop is an open source program under the Apache license maintained by a global community of users. It incorporates various main components, including a MapReduce set of functions and a Hadoop distributed file system.
Predictive analytics is the functional unit of the big data. Most of the firms collect a vast amount of real-time customer data and predictive analytics uses this historical data and combines with customer analysis in order to predict future outcomes. Predictive analytics allows organizations to use big data based on various criteria to study past data and based on this study, it predicts forward-looking perspective of the customer. Big Data sees a huge scope in days to come as predictive analysis is the need for every organisation to grow its business.
Oodles Technologies is a well-built IT company that can serve you with most of your Big Data software solutions. Our development services include open-source Big Data platforms viz. Apache, Hadoop, MongoDB etc. We aim to serve our clients with their varied needs of Big Data Solutions that can ease them enhance their Business reach.