Career advantages of big data data science pdf

Career Advantages of Big Data & Data Science Certifications

Take Your Knowledge to the Next Level with professional enrichment Course Presented By: Xebia India

Career opportunities with having Big Data certification: Here are some job titles that would provide you with full range of opportunities when looking for Big Data-related jobs.  Data  Scientist  Data Engineer  Big Data Engineer  Machine Learning Scientist  Business Analytics Specialist  Data Visualization Developer  Business Intelligence (BI) Engineer  BI Solutions Architect  BI Specialist  Analytics Manager  Machine Learning Engineer  Statistician

The Big Data market grows, so does the demand for skilled workers. Companies today realize the value of

data and analytics and, as a result, they are looking for skilled people to comprehend this data and make sense of it. Job portals like Indeed, Dice, Glassdoor and many more provide a clear picture about the demand for Big Data jobs. Although Big Data is a broad term, it is a commonly used term in job listings, along with data analysts, data scientists and other important roles within the data industry.

According to Wanted Analytics, a best practice insight and technology company, the Big Data skill was mentioned 112,469 times in the first six months of 2015, representing an increase of a 118% over the previous year. Like Big Data, Hadoop is also an extremely broad area. It was mentioned 31,274 times in the first six months of the year and is growing faster with a 118% growth rate.

Introduction of Big Data: Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, updating and information privacy. The term often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. Accuracy in big data may lead to more confident decision making, and better decisions can result in greater operational efficiency, cost reduction and reduced risk.

Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time.

Big data "size" is a constantly moving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data. Big data requires a set of techniques and technologies with new forms of integration to reveal insights from datasets that are diverse, complex, and of a massive scale.

Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on.

Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data sets in areas including Internet search, finance and business informatics. Scientists encounter limitations in e-Science work, including meteorology, genomics, connectomics, complex physics simulations, biology and environmental research.

Data sets are growing rapidly in part because they are increasingly gathered by cheap and numerous information-sensing mobile devices, aerial (remote sensing), software logs, cameras, microphones, radiofrequency identification (RFID) readers and wireless sensor

networks. The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s as of 2012; every day 2.5 exabytes (2.5×1018) of data is created. One question for large enterprises is determining who should own big data initiatives that affect the entire organization.

Applications of Big Data:  Big Data for financial services: Credit card companies, retail banks, private wealth management advisories, insurance firms, venture finds, and institutional investment banks use big data for their financial services. The common problem among them all is the massive amounts of multi structured data living in multiple disparate systems which can be solved by big data. Thus big data is used in a number of ways like:  Customer analytics  Compliance analytics  Fraud analytics  Operational analytics

 Big Data in communications: Gaining new subscribers, retaining customers, and expanding within current subscriber bases are top priorities for telecommunication service providers. The solutions to these challenges lie in the ability to combine and analyze the masses of customer generated data and machine generated data that is being created every day.  Big Data for Retail: Brick and Mortar or an online etailer, the answer to staying the game and being competitive understands the customer better to serve them. This requires the ability to analyze all the disparate data sources that companies deal with every day, including the weblogs, customer transaction data, social media, store branded credit card data, and loyalty program data.

Courses by Xebia Training for Big Data:

1. Cloudera Designing and Building Big Data Applications: Xebia's four-day course from 1st Sep to 4th Sep for designing and building Big data applications prepares you to analyze and solve real-world problems using Apache Hadoop and associated tools in the enterprise data hub (EDH). You will work through the entire process of designing and building solutions, including ingesting data, determining the appropriate file format for storage, processing the stored data, and presenting the results to the end-user in an easy-todigest form. Go beyond Map Reduce to use additional elements of the EDH and develop converged applications that are highly relevant to the business.

Fees- Rs 74400 + applicable tax your lunch has included in this fee.

2. Cloudera Developer Training for Spark and Hadoop I: Xebia's four-day hands-on training course from 15th Sep to 18th Sep delivers the key concepts and expertise participants need to ingest and process data on a Hadoop cluster using the most up-to-date tools and techniques. Employing Hadoop ecosystem projects such as Spark, Hive, Flume, Sqoop, and Impala, this training course is the best preparation for the realworld challenges faced by Hadoop developers.

Participants learn to identify which tool is the right one to use in a given situation, and will gain hands-on experience in developing using those tools.

Fees- Rs 74400 + applicable tax your lunch has included in this fee.

3. Cloudera Administrator Training for Apache Hadoop: Four days course from 22nd Sep to 25th Sep for Apache Hadoop is going to started in Xebia Training. This training provides you with a comprehensive

understanding of all the steps necessary to operate and maintain a Hadoop cluster. From installation and configuration through management, scaling and advanced tuning this training is the best preparation for the real-world challenges faced by Hadoop administrators.

Fees- Rs 74400 + applicable tax your lunch has included in this fee.

4. Cloudera Data Analyst Training: This four days hands-on data analyst training, focusing on Apache Pig and Hive and Cloudera Impala, will teach you to apply traditional data analytics and business intelligence skills to Big Data.

Learn the tools data professionals need to access, manipulate, and analyze complex data sets using SQL and familiar scripting languages.

Fees- Rs 74400 + applicable tax your lunch has included in this fee.