Big data is similar to Small data, but having data bigger consequently requires different approaches, techniques, tools and architecture to solve new problems and old problrms in better way.
Why Big Data is Preferred
-Increase of storage capacities
-Increase of processing power
-Availability of data
Tools used in Big-Data
-No SQL: Database, Couch Db
-Map Reduce: Hadoop, Hive, Cascading
-Storage: S3, Hadoop Distributed File System
-Servers: EC2, Google App Engine
-Processing: R,Yahoo! Pipes
When Big Data is really a hard problem?
-When the operations on data are complex, for example simple counting is not a complex problem.
-Modeling and reasoning with data of different types can get truly complex.
Often, because of vast amount of data, modeling techniques can get simpler, for example smart counting replace complex model based analytics.
Applications of Big Data
1.Health care
The level of data generated within healthcare systems is important. Traditionally, the health care industry fell behind in using Big Data, because of limited ability to standardize and consolidate data.
But now Big data analytics have become better healthcare by providing personalized medicine and dictatorial analytics. Researchers are extracting the data to see what treatments are more effective for particular conditions, identify patterns related to drug side effects, and gains other important information that can help patients and reduce costs.
2.Manufacturing
Predictive manufacturing provides near-zero downtime and transparency. It requires an enormous amount of data and advanced prediction tools for a systematic process of data into useful information.
Major benefits of using Big Data applications in manufacturing industry are:
-Product quality and defects tracking
-Supply planning
-Manufacturing process defect tracking
-Output forecasting
3.Media & Entertainment
Various companies in the media and entertainment are facing new business models, for the way they - create, market and distribute their content. This is happening because of current consumer's search and the requirements of accessing content anywhere, any time, on any device.
Big Data gives actionable points of information about millions of individuals. Now, publishing environments are cutomizing advertisements and content to appeal consumers.
Big Data benefits media and entertainment industry by:
-Predicting what the audience wants
-Scheduling optimization
-Increasing acquisition and retention
-AD targeting
4.Government
The use and adoption of Big Data withing governmental processes allows efficiencies in terms of cost, productivity, and innovation. In government use cases, the same data sets are often applied across multiple applications and it requires multiple departments to work in collaboration.
Advantages of Big Data
1.Cost Saving: Some tools of Big data like Hadoop and Cloud-Based Analytics can bring cost advantages to business when large amounts of data are to be stored and these cost tools also help in identifying more efficient ways of doing business.
2.Time Reduction: The high speed of tools like Hadoop and in-memory analytics can easily identify new sources of data which helps businesses analyzing data immediately and make quick decisions based on the learning.
3.New Product Development: By knowing the trends of customer needs and satisfaction through analytics you can create products according to the wants of customers.
Disadvantages of Big Data
-Traditional storage can cost lot of money to store big data
-lots of big data is unstructured
-Big data analysis violates principals of privacy
-It can be used for manipulation of customer records
-It may increase social stratification
Why Big Data is Preferred
-Increase of storage capacities
-Increase of processing power
-Availability of data
Tools used in Big-Data
-No SQL: Database, Couch Db
-Map Reduce: Hadoop, Hive, Cascading
-Storage: S3, Hadoop Distributed File System
-Servers: EC2, Google App Engine
-Processing: R,Yahoo! Pipes
When Big Data is really a hard problem?
-When the operations on data are complex, for example simple counting is not a complex problem.
-Modeling and reasoning with data of different types can get truly complex.
Often, because of vast amount of data, modeling techniques can get simpler, for example smart counting replace complex model based analytics.
Applications of Big Data
1.Health care
The level of data generated within healthcare systems is important. Traditionally, the health care industry fell behind in using Big Data, because of limited ability to standardize and consolidate data.
But now Big data analytics have become better healthcare by providing personalized medicine and dictatorial analytics. Researchers are extracting the data to see what treatments are more effective for particular conditions, identify patterns related to drug side effects, and gains other important information that can help patients and reduce costs.
2.Manufacturing
Predictive manufacturing provides near-zero downtime and transparency. It requires an enormous amount of data and advanced prediction tools for a systematic process of data into useful information.
Major benefits of using Big Data applications in manufacturing industry are:
-Product quality and defects tracking
-Supply planning
-Manufacturing process defect tracking
-Output forecasting
3.Media & Entertainment
Various companies in the media and entertainment are facing new business models, for the way they - create, market and distribute their content. This is happening because of current consumer's search and the requirements of accessing content anywhere, any time, on any device.
Big Data gives actionable points of information about millions of individuals. Now, publishing environments are cutomizing advertisements and content to appeal consumers.
Big Data benefits media and entertainment industry by:
-Predicting what the audience wants
-Scheduling optimization
-Increasing acquisition and retention
-AD targeting
4.Government
The use and adoption of Big Data withing governmental processes allows efficiencies in terms of cost, productivity, and innovation. In government use cases, the same data sets are often applied across multiple applications and it requires multiple departments to work in collaboration.
Advantages of Big Data
1.Cost Saving: Some tools of Big data like Hadoop and Cloud-Based Analytics can bring cost advantages to business when large amounts of data are to be stored and these cost tools also help in identifying more efficient ways of doing business.
2.Time Reduction: The high speed of tools like Hadoop and in-memory analytics can easily identify new sources of data which helps businesses analyzing data immediately and make quick decisions based on the learning.
3.New Product Development: By knowing the trends of customer needs and satisfaction through analytics you can create products according to the wants of customers.
Disadvantages of Big Data
-Traditional storage can cost lot of money to store big data
-lots of big data is unstructured
-Big data analysis violates principals of privacy
-It can be used for manipulation of customer records
-It may increase social stratification
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