The Big Data and Hadoop Training in Los Angeles will equip you with in-depth knowledge of Big Data’s framework using tools such as Hadoop and Spark. With Big Data and Hadoop training in Los Angeles, students are given the opportunity toemploy the Integrated Lab to solve real-world, industry-relevent problems. This exercise provides Big Data work experience.
Lifetime access to self-paced e learning content
Give your career the lift it needs by taking Big Data and Hadoop Training in Los Angeles. The opportunities are lucrative: the global HADOOP-AS-A-SERVICE (HAAS) Market in 2019 was USD 7.35 Billion and promises to keep growing. Many believe the market will grow at a CAGR of 39.3%, increasing to USD 74.84 Billion by 2026. To remain relevant in the industry, Big Data and Hadoop Training in Los Angeles is important.
Online Classroom:
Online Self-Learning:
To become Certified Big Data Hadoop Developer, you must fulfill both of the following criteria:
Simplilearn’s Hadoop Certifications Training in Los Angeles is Classroom Flexi-Pass Learning Methodology that has a validity of 180 days (6 months) of high-quality e-learning videos, Self-paced learning Content plus 90 days of access to 9+ instructor-led online training classes.
Simplilearn’s Hadoop Certification course in Los Angeles is priced at $999 for Online Classroom Flexi-Pass.
There are no prerequisites for learning this course. However, knowledge of Core Java and SQL will be beneficial, but certainly not a mandate. If you wish to brush up your Core-Java skills, Simplilearn offers a complimentary self-paced course "Java essentials for Hadoop" when you enroll for this course. For Spark, this course uses Python and Scala, and an e-book is provided to support your learning.
It takes around 45-50 hours to successfully complete the Big Data and Hadoop training in Los Angeles.
The global Big Data and data engineering services market is expected to grow at a CAGR of 31.3 percent by 2025, so this is the perfect time to pursue a career in this field.
The world is getting increasingly digital, and this means big data is here to stay. The importance of big data and data analytics is going to continue growing in the coming years. Choosing a career in the field of big data and analytics might be the type of role that you have been trying to find to meet your career expectations. Professionals who are working in this field can expect an impressive salary, the median salary for a data engineer is $137,776, with more than 130K jobs in this field worldwide. As more and more companies realize the need for specialists in big data and analytics, the number of these jobs will continue to grow. A role in this domain places you on the path to an exciting, evolving career that is predicted to grow sharply into 2025 and beyond.
According to Forbes, Big Data & Hadoop Market is expected to reach $99.31B by 2022.
This Big Data Hadoop certification course in Los Angeles is designed to give you an in-depth knowledge of the Big Data framework using Hadoop and Spark, including HDFS, YARN, and MapReduce. You will learn to use Pig, Hive, and Impala to process and analyze large datasets stored in the HDFS, and use Sqoop, Flume, and Kafka for data ingestion with our significant data training.
You will master Spark and its core components, learn Spark’s architecture, and use the Spark cluster in real-world - Development, QA, and Production. With our Big Data Hadoop course, you will also use Spark SQL to convert RDDs to DataFrames and Load existing data into a DataFrame.
As a part of the Big Data Hadoop course, you will be required to execute real-life, industry-based projects using Integrated Lab in the domains of Human Resource, Stock Exchange, BFSI, and Retail & Payments. This Big Data Hadoop training course in Los Angeles will also prepare you for the Cloudera CCA175 significant Hadoop certification exam.
Big Data Hadoop certification training in Los Angeles will enable you to master the concepts of the Hadoop framework and its deployment in a cluster environment. By the end of this course, you will be able to:
Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology in Big Data architecture. Big Data training in Los Angeles is best suited for IT, data management, and analytics professionals looking to gain expertise in Big Data, including:
The Big Data Hadoop Training course in Los Angeles includes four real-life, industry-based projects. Following are the projects that you will be working on:
Project 1: Analyzing employee sentiment
Objective: To use Hive features for data analysis and sharing the actionable insights into the HR team for taking corrective actions.
Domain: Human Resource
Background of the problem statement: The HR team is surfing social media to gather current and ex-employee feedback or sentiments. This information gathered will be used to derive actionable insights and take corrective actions to improve the employer-employee relationship. The data is web-scraped from Glassdoor and contains detailed reviews of 67K employees from Google, Amazon, Facebook, Apple, Microsoft, and Netflix.
Project 2: Analyzing Intraday price changes
Objective: To use hive features for data engineering or analysis and sharing the actionable insights.
Domain: Stock Exchange
Background of the problem statement: NewYork stock exchange data of seven years, between 2010 to 2016, is captured for 500+ listed companies. The data set comprises of intra-day prices and volume traded for each listed company. The data serves both for machine learning and exploratory analysis projects, to automate the trading process and to predict the next trading-day winners or losers. The scope of this project is limited to exploratory data analysis.
Project 3: Analyzing Historical Insurance claims
Objective: To use the Hadoop features for data engineering or analysis of car insurance, share patterns, and actionable insights.
Domain: BFSI
Background of the problem statement: A car insurance company wants to look at its historical data to understand and predict the probability of a customer making a claim based on multiple features other than MVR_POINTS. The data set comprises 10K plus submitted claim records and 14 plus features. The scope of this project is limited to data engineering and analysis.
Project 4: Analyzing Product performance
Objective: To use the Big data stack for data engineering for the analysis of transactions, share patterns, and actionable insights.
Domain: Retail & Payments
Background of the problem statement: Amazon wants to launch new digital marketing campaigns for various categories for different brands to come up with new Christmas deal to:
1. Increase their sales by a certain percentage.
2. Promote products which are the least selling
3. Promote products which are giving more profits
They have provided a transactional data file that contains historical transactions of a few years along with product details across multiple categories. As an analytics consultant, your responsibility is to provide valuable product and customer insights to the marketing, sales, and procurement teams. You have to preprocess unstructured data into structured data and provide various statistics across products or brands or categories segments and tell which of these segments will increase the sales by performing well and, which segments need an improvement. The scope of this project is limited to data engineering and analysis.
The field of big data and analytics is a dynamic one, adapting rapidly as technology evolves over time. Those professionals who take the initiative and excel in big data and analytics are well-positioned to keep pace with changes in the technology space and fill growing job opportunities. Some trends in big data include: