What is Big Data?
The origins of large data is 1960 and in 2005, People began to realize just how much data users generated through Facebook, YouTube, and other online services. Big data is one of the most valuable product right now to earn money. This world has turned into data world now these days.
Big Data is a collection of data that is large in amount and everyday the size of this data is drastically increasing. As this data is in large amount and full of complexity, not a single traditional data management tools is able to store it or process it efficiently.
Types Of Big Data
Characteristics Of Big Data
What is the use of Big Data?
Big data can help you track range of business activities, from customer experience to analytics. some of them are given below.
- Product development – Almost all companies use big data to predict customer demand or services and modeling the link between those attributes and the commercial success of the offerings.
- Predictive maintenance – Factors that can predict mechanical failures may be deeply buried in structured data, such as the year, make, and model of equipment, as well as in unstructured data that covers millions of log entries, sensor data, error messages, and engine temperature. By analyzing these indications of implicit issues before the problems takes place, companies can deploy maintenance more cost effectively and maximize elements and equipment uptime.
- Customer experience – The race for making customers experience good is on. A crystal clear view of customer experience is more possible now than ever before. Big data helps you to collect data from social media, web visits, call logs, and other sources to improvise the interaction experience and maximize the value delivered. Start delivering personalized offers, minimize customer churn, and manage issues proactively.
- Fraud and compliance – When it comes to security, it’s not just a hacker you’re up against but the entire expert teams. Security landscapes and compliance requirements are continuously emerging. Big data helps you seeks patterns in data that indicate fraud and aggregate large volumes of information to make regulatory reporting much faster.
- Machine learning – Machine learning is a widely spreaded hot topic for now. And data specifically big data is one of the reasons why we are now able to teach machines except of program them. The availability of big data to train machine learning models makes that possible.
Operational efficiency may not being in news, but it’s an area in which big data is having the most impact. With big data, you can analyze and assess production, customer feedback and returns, and other factors to reduce outages and anticipate future demands. Big data can also be used to improve decision-making in line with current market demand.
- Drive innovation – Big data can help you innovate by studying interdependencies among humans, institutions, entities, and process and then determining new ways to use those insights. Use data insights to improve decisions about financial and planning considerations. Examine trends and what customers want to deliver new products and services. Implement dynamic pricing. There are endless possibilities.
Compare Big Data Vs data science Certification
|Data Science||Big Data|
|Data Science is an area.||Big Data is a technique to collect, maintain and process the huge information.|
|It is about collection, processing, analyzing and utilizing of data into various operations. It is more conceptual.||It is about extracting the vital and valuable information from huge amount of the data.|
|It is a field of study just like the Computer Science, Applied Statistics or Applied Mathematics.||It is a technique of tracking and discovering of trends of complex data sets.|
|The goal is to build data-dominant products for a venture.||The goal is to make data more vital and usable i.e. by extracting only important information from the huge data within existing traditional aspects.|
|It is a super set of Big Data as data science consists of Data scrapping, cleaning, visualization, statistics and many more techniques.||It is a sub set of Data Science as mining activities which is in a pipeline of the Data science.|
|Tools mostly used in Big Data includes Hadoop, Spark, Flink, etc.||Tools mainly used in Data Science includes SAS, R, Python, etc|
|It is mainly used for scientific purposes.||It is mainly used for business purposes and customer satisfaction.|
|It broadly focuses on the science of the data.||It is more involved with the processes of handling voluminous data.|
List of Big Data Certification
- Cloudera Certified Professional
- DevOpsSchool Big Data Hadoop Certification
- Microsoft’s MCSE: Data Management and Analytics
- Hortonworks Hadoop Certification
- MongoDB Certified Developer
- EMC Data Science and Big Data Analytics Certification
- SAS Certified Data Scientist
- Data Science Council of America Certification
- Oracle Business Intelligence Certification
- Mining Massive Data Sets Graduate Certificate
Big Data Certification Path
Become Big Data hadoop certified professional by getting trained from DevOpsSchool.
Big Data Certification Cost
- Cloudera Certified Professional – US$295
- DevOpsSchool Big Data Hadoop Certification – Rs 49,999
- Microsoft’s MCSE: Data Management and Analytics – $149 USD
- Hortonworks Hadoop Certification – US$250
- MongoDB Certified Developer Exam – US$150
- EMC Data Science and Big Data Analytics Certification – US$600 for video-ILT streaming; US$5,000 for instructor-led
- SAS Certified Data Scientist – $970
- Data Science Council of America Certification – US$520
- Oracle Business Intelligence Certification – US$245
- Mining Massive Data Sets Graduate Certificate – $149 USD
Best salary for Big Data Certified Professional
An entry-level Big Data Engineer’s salary is around ₹466,265 annually. An early-career Big Data Engineer or a Junior Big Data Engineer’s salary (1–4 years of experience) is an average of ₹722,721 p.a. A mid-career Big Data Engineer or Lead Big Data Engineer salary (5–9 years of experience) is ₹1,264,555 per year.
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