About our program that encompasses big data engineer training in Mountain View, created in collaboration with IBM
IBM is a pioneer in the technology industry, and they continue to be one of the world’s top technology brands. IBM is the second-largest machine learning and predictive analytics provider in the world. Each year, they invest $6 billion into development and research directly related to technology to support its fast growth.
IBMachievements and accomplishments have given them many global laurels - six Turing Awards, five U.S. National Medals of Science, five Nobel Prizes, 10 inductions in the U.S. Inventors Hall of Fame and nine U.S. National Medals of Technology.
Together, IBM and Simplilearn have worked closely together in the development of our big data engineer training in Mountain View. This program is perfect for anyone looking to pursue a career in big data, data engineering, or other technology sectors.
What can I expect from this big data engineer training in Mountain View that was designed with IBM?
Earn two certificates from Simplilearn and IBM after successfully completing our big data engineer training in Mountain View. Given the hyper competitive job market in this field, these valuable credentials you get can catapult you ahead of your competitors and give you a clear edge in the data engineering career journey. Students also receive:
Our big data engineer training in Mountain View offers in-depth instruction on big data frameworks and other relevant technologies. Because big data is offered in numerous industries and organizations worldwide, it is an extremely valuable skill to have. Organizations everywhere increasingly rely on data for decisions on their business, and 2025 is expected to bring in unprecendented growth in this area.
In this course, students learn about the various programs and techniques needed to thrive as professional big data engineers. Our program also teaches ingestion performance, replicating and modeling data, database management system use, and more. Software technology topics are concentrated on Mongo DB, Scala, Flume, Pig, Spark ML, Advanced Architecture, Hive, Impala, Data Model Creation, etc.
After enrolling in our big data engineer training in Mountain View, you’ll gain knowledge on the Hadoop ecosystem, a crucial component of big data engineering. This includes learning tools like MapReduce, Pig, Impala, HBase, Sqoop, and others. Upon completion of the big data engineer training in Mountain View, you’ll be able to:
The big data engineer training in Mountain View curriculum includes more than a dozen projects that mirror scenarios that big data engineers often handle. These projects teach clusters, configuration, scalability, and other key principles of data engineering. Examples of projects include:
Project 1: Set up big data clusters the same way big companies do
Project Title: Scalability-Deploying Multiple Clusters
Description: You’ve been tasked with creating a new cluster on a newly purchased system. Due to the time-consuming nature of setting up these new systems, you'll requirement for creation of the new cluster in the existing systems. Your organization also wants you to start testing that the new cluster applications are adequately working.
Project 2: Use big data clusters the same way large organizations do
Project Title: Working with Clusters
Description: In this project for big data engineer training in Mountain View, you will demonstrate your comprehension of the following:
Project 3: Demonstrate how financial institutions and banks use big data when analyzing their competitors
Domain: Banking
Description: A Portuguese bank created a marketing campaign to target consumers wanting to invest in a bank term deposit. The campaign saw phone calls (sometimes multiple calls) to consumers, and task at hand is to gather and analyse the data generated.
Project 4: Utilize big data and focus on telecommunications to understand how telecom giants, such as AT&T, leverage data for various purposes
Domain: Telecommunication
Description: A mobile provider has a newly launched Open Network campaign, and customers were encouraged to submit complaints regarding local towers if they have service interruption or signal problems. Customers who did experience these difficulties submitted relevant information and this data was collected accordingly. The fourth and the fifth field of this information include the latitude and longitude of customers, which is important information for the mobile provider to have. You are tasked with identifying the latitude and longitude information on the basis of the available data and develop three clusters of users with a k-means algorithm.
Project 5: Learn how major streaming services, such as Netflix and Amazon Prime, use big data
Domain: The movie industry
Description: A United States-based university has collected data from various movie reviews as a part of a research project. Utilizing Spark, you will execute multiple activites with the data possessed to generate in-depth insights from the project that is included in this big data engineer training in Mountain View.
Project 6: Learn how Simplilearn and other online schools use NoSQL and big data
Domain: E-learning industry
Description: Design a web application for a top online education program with MongoDB to support read and write scalability. Java, HTML, and Servlet are some of the different online technologies that can be used when creating this web application. Users should also be able to access, delete, edit, and add course data using MongoDB as the backend database.
Our big data engineer training in Mountain View is ideal for students looking to pursue a career in data engineering. There are no requirements to qualify for our training program, but experience or comprehension in any of the following can be beneficial:
On receipt of this big data engineer training in Mountain View, that is offered as an IBM collaboration, you stand to grab the best opportunites in the job roles mentioned below:
This course from IBM will teach you the basic concepts and terminologies of Big Data and its real-life applications across industries. You will gain insights on how to improve business productivity by processing large volumes of data and extracting valuable information from them.
Simplilearn’s Big Data Hadoop course lets you master the concepts of the Hadoop framework, Big data tools, and methodologies. Achieving a Big Data Hadoop certification prepares you for success as a Big Data Developer. This Big Data and Hadoop training help you understand how the various components of the Hadoop ecosystem fit into the Big Data processing lifecycle. Take this Big Data and Hadoop online training to explore Spark applications, parallel processing, and functional programming.
Get ready to add some Spark to your Python code with this PySpark certification training. This course gives you an overview of the Spark stack and lets you know how to leverage the functionality of Python as you deploy it in the Spark ecosystem. It helps you gain the skills required to become a PySpark developer.
Simplilearn’s Kafka certification lets you explore how to process huge amounts of data using various tools. You will understand how to better leverage Big data analytics with this Kafka training. Take advantage of our blended learning approach for this Kafka course and learn the basic concepts of Apache Kafka. Get ready to go through the cutting-edge curriculum of this Apache Kafka certification designed by industry experts and develop the job-ready skills of a Kafka developer.
Simplilearn’s MongoDB certification equips you with the relevant skills required to become a MongoDB Developer. The highly-qualified instructors for this MongoDB course help you understand why more businesses are using MongoDB development services to handle their increasing data storage and handling demands. Our MongoDB training is equipped with industry projects, lab exercises and various demos to explain key concepts. Enroll in our MongoDB online course and learn this popular NoSQL database
Simplilearn’s AWS Data Analytics certification training prepares you for all aspects of hosting big data and performing distributed processing on the AWS platform. Our AWS data analytics course is aligned with the AWS Certified Data Analytics Specialty exam and helps you pass it in a single try. Developed by industry leaders, this AWS certified data analytics training explores some interesting topics like AWS QuickSight, AWS lambda and Glue, S3 and DynamoDB, Redshift, Hive on EMR, among others
Simplilearn’s Big Data Capstone project will give you an opportunity to implement the skills you learned in the Big Data Engineer training. With dedicated mentoring sessions, you’ll know how to solve a real industry-aligned problem. The project is the final step in the learning path and will help you to showcase your expertise to employers.
Our Master's program is exhaustive and this certificate is proof that you have taken a big leap in mastering the domain.
The knowledge and skills you've gained working on projects, simulations, case studies will set you ahead of competition.
Talk about your certification on LinkedIn, Twitter, Facebook, boost your resume, or frame it - tell your friends and colleagues about it.
Big data engineering is an important aspect of data science that involves building, maintaining, testing, and assessing big data solutions. It emphasizes the development of systems that allow for better flow and access to the data. It also incorporates the collection of data of disparate sources, cleaning, and processing data to make it ready for analysis.
A Big Data Engineer prepares data for analytical or operational uses. Their primary roles include building data pipelines to collect information from various sources, integrating, combining, cleaning, and using data for individual analytics applications. Their role evolves from collecting and storing data to transforming, labeling, and optimizing data.
Big Data Engineers often work with data scientists who run queries and algorithms against the collected information for predictive analysis. They also work with business units to deliver data aggregations to executives. Big Data Engineers commonly work with both structured and unstructured data sets, for which they must be well-versed in different data architectures, applications, and programming languages such as Spark, Python, and SQL.
This Big Data Engineer course developed in collaboration with IBM will give you insights into the Hadoop ecosystem, Data engineering tools, and methodologies to prepare you for success in your role as a Big Data Engineer. The industry-recognized certification from IBM and Simplilearn will attest to your new skills and on-the-job expertise. This course will train you on Big Data, Hadoop clusters, MongoDB, PySpark, Kafka architecture, SparkSQL, and much more to become an expert as Big Data Engineer.
As a part of this Big Data Engineer course, developed in collaboration with IBM you will receive the following:
Lifetime access to e-learning content for all of the courses included in the learning path (*only for Simplilearn courses)
Industry-recognized certificates from IBM(for IBM courses) and Simplilearn upon successful completion of the course
Access to IBM cloud platforms featuring IBM Watson and other software for 24/7 practice
You will get an IBM certificate for the first course present in the Big Data Engineer course curriculum.
Upon completion of the following minimum requirements, you will be eligible to receive the Master’s certificate that will testify to your skills as a Big Data Engineer.
Course |
Course Completion Certificate |
Criteria |
Big Data for Data Engineering |
Required |
85% of online self-paced completion |
Big Data Hadoop and Spark Developer |
Required |
85% of online self-paced completion OR attendance of one Live Virtual Classroom, AND score above 75% in course-end assessment AND successful evaluation in at least one project |
PySpark Training |
Required |
85% of online self-paced completion |
MongoDB Developer and Administrator |
Required |
85% of online self-paced completion OR attendance of one Live Virtual Classroom, AND score above 75% in course-end assessment AND successful evaluation in at least one project |
Apache Kafka |
Required |
85% of online self-paced completion |
Big Data on AWS |
Required |
Attendance of one Live Virtual Classroom AND successful evaluation in at least one project |