Big Data Now a days

Introduction To Big Data Nowadays

Big Data + Hadoop Ecosystem(Data Science) refers to mine information from a huge collection of structured, unstructured and semi-structured data. Data usually exists in huge amount but some time we just need to extract some useful information or small amount of data sets. It usually characterized by 3 V’s huge volume of data, large variety of data and the velocity of the data the time on which data processed. It evolves data analytic, data science to predict the business results and other quality predictions.

Big Data+ Hadoop Ecosystem(Data Science) Analytic:

Big data +Hadoop EcoSystem analytic is all about to analyze the raw data to get useful information in order to use it in particular way to produce business results. On an expensive scale, data analytic tools and technique provide a major way to draw conclusions and extract useful information from huge amount of data sets which helps organizations to make quality decisions.

How Big Data + Hadoop EcoSystem Works?

We are living in a era of Big Data + Hadoop Eco System(Data Science). Businesses are not simply collecting the data that we are generating actually they analyze the data to find the way to generate or improve their products and services. The data somewhere stores and then data scientists pick that data and analyzed to make prediction. Technology produces data whenever we chat with our friends or relatives online or buy anything online we actually generating the data in huge amount and leaving the sources and it comes and happens in real world within no time.

Businesses use all these data and analyze to produce the customize results.This is all about Big Data + Hadoop Eco System it’s all the data that generated in digital era through different types of technologies.

Apache Hadoop and Apache Hive:

Apache Hadoop is a open source framework to handle huge amount of data nodes in it. It’s quite difficult to install. To install it you must have the latest version of the JDK. Big Data +Hadoop EcoSystem(Data Science) stores and then processed on the large amount of data to generate quality results.

Hadoop is made up of “modules” each module has its own task and necessary for system designed for data analytic.

1. HDFS (Hadoop Distributed File System )
2. Mapreduce 

     Mapreduce is a combination of two words Map and Reduce reading data from the database and put into analyzed from is mapping and performing the statistical and mathematical operations is Reducing. 

1. Hadoop Common
2. YARN

Apache hive is another platform for providing open source services for Big Data. Hive gives SQL interface to handle the queries and stores it like Hadoop that just processed on the queries but does not store. Hive is a structural database that provides facility to convert unstructured data into structured data. Table schema is applied in this technique.

Advantages of Big Data in Business:

The use of huge knowledge is changing into common recently by the businesses to outdo their peers. In most industries, existing competitors and new entrants alike can use the ways ensuing from the analyzed knowledge to increase their prices.

Here are some key advantages of Big Data:

1. Better Decision Making: BI is used to make much better decisions in the modern era.
2. Increased productivity: Most of the users use big data tools like Hadoop and Spark to increase the productivity. Modern tools allow the users to generate more quality results in an efficient manner.
3. Reduce Cost

Fraud Detection: Machine learning techniques will be used when we need some kind of predictions. If a company wants to build a scenario for their customers to secure them from fraud. This kind of scenario could fall under supervised learning because we already of training data sets of previously recorded information of their customers. Through this training data sets we can train our machines more advance for prediction. For instance, a bank can detect fraud b using their machines as from their fraudulent actions.

1. Increased Revenue: When organizations use their big data strategy to improve their decision making technology for their customer services automatically more revenue is the often result.

Business Intelligence Vs Data Science:

Majority of people mix up the term Data science vs Business Intelligence these two are individual fields.

BI basically analyze the past data to generate the depth results of businesses trend. On the other hand, data science evolves using previous and current data sets and predicting the future outcomes of well organized business needs. It usually focuses on what and how and why the things occur. Data science evolves machine learning techniques for predict the future outcomes and make the better decisions.

Future of Big Data:

However, Big Data has become the core head of Information Technology and play an important role in every business. Installation of its machinery is quite difficult that’s why its developers charge almost 25 to 50 Dollars to create and ready the complete machinery.

That’s why it gain much popularity in IT because in every decision making environment it should play an important role.

Reasons to learn Big Data:

1. Data driven decisions lead to the advantages: Big data allows organizations to detect fraud, patterns that could be used for future benefits. It can help customers to lead in effective manner.
2. Big data provides a leading way for AI: Big data provides a foundation to start AI projects.
3. Demand of Big Data Developer: As the data is increasing day by day that’s why to manage this huge amount of data professional skilled developer of Big Data required.
4. Rapidly Increase of the Investment: Big data industry growing vary rapidly. Big data is becoming a trend now a days, for predicting the most close predictions.