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Big Data Certification
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Uplatz is well known for providing instructor-led training and video-based courses on SAP, Oracle, Salesforce, AWS, Big Data, Machine Learning, Python, R, SQL, Google & Microsoft Technologies, and Digital Marketing.
SAP and AWS training courses are currently the most sought-after courses globally.
An SAP consultant on an average earns a package of $80,000 ($100,000) per annum based on the skills and experience.
To learn this course -
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Master the various components of Hadoop ecosystem like Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark. Get hands-on practice on CloudLabs by implementing real life projects in the domains of banking, telecommunication, social media, insurance, and e-commerce. The course is aligned to Cloudera CCA175 certification. This course is best suited for IT, data management, and analytics professionals looking to gain expertise in Big Data.
Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples. Systems and tools discussed include: AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. This course provides techniques to extract value from existing untapped data sources and discovering new data sources.
Big Data Certification
At the end of this Big Data Certification training course, you will be able to:
* Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors.
* Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting.
* Get value out of Big Data by using a 5-step process to structure your analysis. * Identify what are and what are not big data problems and be able to recast big data problems as data science questions.
* Provide an explanation of the architectural components and programming models used for scalable big data analysis.
* Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model.
* Install and run a program using Hadoop!
This course is for those who are relatively new to data science. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments.
