Big Data & Data Science

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We are incepted on a mission of rendering the Best Big Data Analytics Training and Data Science Training in Hyderabad, India. Our customized Big Data Course Training and Data Science and Machine Learning Training Essentials are curated by subject matter experts who have a great hands-on experience in the IT Industry. This renders the students with an explicit learning and hands-on experience for pursuing a career in Hadoop Development Tools, Spark Development, Big Data Analytics, Data Science Development, Artificial Intelligence, Data Visualization, statistics and analysis. For More Info:


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slide 1: Digital Nest +91-8088998664 Page 1 Many IT experts around the globe would agree that we live in the age of Big Data. Data Science and Big Data are the two terms commonly referenced in all literature while discussing the potential benefits of enabling data driven decision making. Importantly these latest trends are creating new job opportunities and the demand for the people with right set of data skills is on the rise. In order to meet the growing need for Big Data and Data Science talent we are witnessing the emergence of traini ng programs across worldwide universities MOOCs and other niche analytics institutes. At Jigsaw Academy we have specially created Data Science and Big Datacourses with the help of industry experts to guide aspiring students and working professionals pursue successful careers in a fascinating data world. Though these courses fall under the broad category of the data analytics field some major differences exist between them in terms of technologies involved and the vast possibilities of end applications. Data Science course involves the execution of different phases of analytics projects such as data manipulation visualization and predictive model building using R software. This course also provides training on general programming with R using in-built data objects and also on writing custom functi ons and programs. On the other hand the Big Data course majorly deals with processing and analyzing massive amounts of data using Hadoop technology. Traditional database systems fall short in dealing with Big Data effectively and thus adoption of NoSQL based systems such as Hadoop and others across many industry verticals is increasing. Apart from providing both theoretical and hands on aspects of working with Hadoop this course also covers performing data analysis using software’s such as R and Tableau. One other key modules of the Big Data course would be on integration of R and Tableau with Hadoop cluster to make best of both the worlds. In Hadoop infrastructure enables smooth handling of big data whereas R and Tableau in built functions help in generating insights from data through summary statistics dashboards and visualizations. In the next sections I will discuss in more detail about some of the key differences between Data Science and Big Data courses in terms of tool exposure coverage of topics related to statistics and advanced analytics. Additionally various aspects related to the course choice in terms of career

slide 2: Digital Nest +91-8088998664 Page 2 fit will be discussed including comparisons of the existing Big Data course offered by EMC and Cloudera Hadoop certification. How do Data Science and Big Data courses differ from each other To better understand the differences between these courses one should try to look at some of the key dimensions such as the kind of tools and technologies that can be learnt and the extent of big data concepts that will be covered in each of them. Building a comprehensive working knowledge and expertise around various analytical and database tools is a key step to excel in Big Data and Data Science fields. The Data Science course is entirely taught in R software which is an open source statistical programming language and one of the essential tools that are a part of any Data Scientist’s Tool Kit. Due to its extensive package repository around statistical and analytics appl ications R is tremendously growing in popularity around the world and many firms are on the lookout for R programmers. Take a look at what some of our students have to say about the Data Science course.

slide 3: Digital Nest +91-8088998664 Page 3 On the other hand Jigsaw’s Big Data course provides extensive training on Hadoop and its components such as Hive HBase Sqoop and Flume to process and analyze large amounts of data. This course also covers installation aspects of Hadoop along with its components and trains students on Java based MapReduce programming. Apart from Hadoop concepts Big Data course also contains training modules on integration of R and Tableau software’s with Hadoop cluster using RHadoop library and Tableau-Hadoop connectors to perform data analysis tasks and further generate dashboards and visualizations. Find out more about the topics covered in the 5 modules of the Big Data Training using Hadoop course. Statistics and advanced analytics techniques knowledge is crucial fo r implementing successful data analytics projects. The Data Science course covers these topics in a comprehensive manner with applications of R programming. Typically an analytics project consists of various phases such

slide 4: Digital Nest +91-8088998664 Page 4 as manipulation preparation exploration and visualization on different kinds of business data. Along with training modules on these phases predictive analytics techniques like regression models clustering and decision trees are covered using real time case studies. Additional training modules around time series techniques and text analytics are also covered which helps in processing specific kinds of data such as text and social media content. In the Big Data course the emphasis will be more on handling and analysing huge volumes of data to generate insights through summarization and visualization techniques. Instead of advanced analytics techniques this course puts more emphasis on BI aspects such as exploratory analysis building dashboards and visualizations. Since Big Data technologies like Hadoop is a complex system compared to traditional SQL based systems most of the learning modules will focus on data handling and processing using various components of Hadoop ecosystem such as MapReduce programming using Java querying using Hiv eQL or scripting using Pig. Since Big Data skills are a hot skill to have now and every business is actively looking out for the right talent both the Big Data and Data Science courses consists of learning modules specific to working with

slide 5: Digital Nest +91-8088998664 Page 5 Hadoop. The Data Science course provides an overview of Hadoop technology and writing Map Reduce programs through R and Hadoop integration using R Hadoop library. These libraries are designed and developed by Revolution Analytics majorly for R programmers who can interact with Hadoop cluster through R syntax whenever such a need occurs. On the other hand Big Data course is all about Hadoop data processing and further how one can integrate tools such as R and Tableau with Hadoop for performing data analysis. More than half of the learning modules provide both technical and hands on knowledge related to configuration and data processing using Hadoop and its various components such as HBase Hive Flume and Sqoop. Regards the case studies dealt with in the courses both the Big Data and Data Science courses differ in terms of end applications with the former focusing more on massive datasets and the latter focusing more on predictive analytics problems. In the Data Science course the concepts of predictive analytics techniques using R software across industry verticals such as retail finance and telecom are used. Some of the examples of these business problems are prediction of telecom churn sale price of cars credit risk behaviour and marketing mix modelling. Even in the Big Data course the emphasis would be more on analytics rela ted problems across various domains such as exploratory analyses and visualizations along with installation and configurations aspects of Hadoop cluster. On the analytics side text mining would be covered extensively as Hadoop technologies are more popular in dealing with unstructured data problems. Some of the problems that will be covered are around social media analytics with twitter data web analytics on click stream data and financial analysis using stock data.

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