Online Classroom Batches Preferred
(Class 1Hr - 1:30Hrs) / Per Session
(Class 1Hr - 1:30Hrs) / Per Session
(Class 3hr - 3:30Hrs) / Per Session
(Class 4:30Hr - 5:00Hrs) / Per Session
No Interest Financing start at ₹ 5000 / month
Overview of Big Data Analytics Online certification Training
The Big Data course will expose you to popular big data technologies, including demos and case studies for each. The training will concentrate on using each of these technologies for analytics reasons. It will begin with a briefing on Hadoop, covering the framework and its many versions.
Learn and advance your career with our Big Data Analytics Training:
- Big Data analytics is the process of collecting, managing, and analysing large data collections (Big Data) in order to identify patterns and other relevant information.
- In this course on Big data analytics, you will enhance your knowledge of big data analytics and your programming and mathematical abilities. You will learn how to utilise important analytic tools such as Apache Spark and R.
- You gain an understanding of predictive analytics, including probabilistic and statistical models.
- These patterns are a treasure trove of information, and their analysis yields several insights that organisations can use to make business decisions.
- The course covers fundamental concepts and technologies, such as simple linear regression, prediction models, deep learning, and machine learning, among others.
- In addition, to enhance your learning experience, we will assign you to real-world industry initiatives.
Tools used for Big Data Analytics:
There are a lot of big data analytics tools on the market today, but choosing the right one depends on what a business needs, what its goals are, and what kinds of data it has.
APACHE Hadoop: Hadoop is an open-source tool built on Java that is used to store and handle large amounts of data. It is made with a cluster system, which lets the system handle data quickly and let data run at the same time. It can send both organized and random data from a single server to multiple computers. Hadoop also lets its users use it on more than one device. It is now the best tool for analyzing big data, and tech giants like Amazon, Microsoft, IBM, etc. use it.
APACHE: Cassandra The open-source NoSQL distributed database Cassandra is used to get a lot of information. It's one of the most well-known tools for data analytics, and more tech companies like it because it can be used in more places and can be scaled up without affecting speed or performance.
Qubole: Qubole is an open-source big data tool for doing ad hoc analysis in machine learning, which can then be used to acquire data from the value chain. Qubole is a tool for data lakes that gives end-to-end service and makes moving data flows take less time and work. It can set up services from multiple clouds, such as AWS, Azure, and Google Cloud. In addition, it helps cut the cost of cloud computing by 50%.
Xplenty: Xplenty is a tool for analyzing data that helps you build a data flow with as few lines of code as possible. It gives a lot of options for sales, marketing, and customer service. It offers options for ETL, ELT, etc. by using a dynamic graphics user interface. The best thing about using Xplenty is that it requires little investment in gear and software and offers help through email, chat, phone, and online meetings. Xplenty is the tool for analyzing data over the cloud, and it puts all of the data together.
Spark: APACHE Spark is another system that is used to handle big amounts of data and do many different jobs. With the help of spreading tools, it is used to process data on several computers at the same time. It is used by data scientists because it has easy-to-use APIs that make it easy to pull data, and it can also handle a lot of data (multi-petabytes worth). It lets people run in the language they want. (JAVA, Python, and so on).
Features of Big Data Analytics:
- The initial phase in a data analysis is called data exploration, and it involves for looking at and visualizing data to find the insights right away or point out regions or patterns that need to be further investigation. Users may gain insights by using an interactive dashboards and point-and-click of data exploration to the best understand a broader picture.
- To scale up, or vertically scale, a system, a faster server with the more powerful processors and memory is needed. This technique are utilizes less network gear and uses less energy, but it may only be temporary cure for more big data analytics platform characteristics, especially if a more growth is anticipated.
- The process of obtaining, storing, and using to data in the cost-effective, effective, and secure way is known as a data management. Data management assists people, organizations, and connected things optimizing the use of data within bounds of policy and regulation, enabling decision-making and actions that will benefit business as much as feasible. As businesses increasingly rely on intangible assets to be create value, an efficient data management strategy is much important than be ever.
- Data integration is process of combining information from a several sources to give people cohesive perspective.When done correctly, data integration can enhance the data quality, free up resources, lower IT costs, and stimulate to creativity without significantly modifying a current applications or data structures. Aside from fact that IT firms have been always needed to integrate, benefits of doing so may have never been as large as they are now.
- It's a more crucial than ever to have simple ways to see and comprehend a data in increasingly data-driven environment.Data and its ramifications must be understand by all the employees and business owners.
Skills covered in this Big Data Analytics:
Predictive analytics: Predictive analytics, which includes predicting and modeling different events and results, is becoming a key part of understanding the art and science of big data. This method uses mathematical tools to look for trends in current or new data to predict future events, customer behavior, and financial results.Predictive analytics can be used and put to use in many different businesses.
Quantitative analysis: Because it is based on arithmetic, particularly calculus and linear algebra, quantitative analysis is a component of big data. The big data professional's skills and knowledge in these areas will give them a head start in understanding statistics and algorithms, which are essential for doing well in big data jobs. Tools like SAS, IBM SPSS Statistics, and the R language are important for professionals to know how to use.
Data visualization: It's more important to be able to present results in an interesting and convincing way. Therefore, a data visualization is essential part of toolkits. A Professionals who are the most effective in an efforts of typically use attention-grabbing graphics and charts to them in presenting a findings clearly and succinctly.
Data mining: By using the software to find a patterns in large batches of a collected data, businesses can gain granular insights of customers. This enables them to develop a more targeted and personalized marketing strategies, drive up to sales and cut costs. Expertise in a data mining tools and technologies is high demand when it comes to be securing big data jobs. A Proficiency in the tools like RapidMiner, Apache Mahout and Knime .
Future role for Big Data Analytics developer
- On-premises and cloud environments are supported by a data fabrics, which can provide a consistent functionality across the variety of endpoints. Using a Data Fabric, organizations can simplify and integrate a data storage across the cloud and on-premises environments, providing access to and sharing of a data in a distributed environment to drive the digital transformation & new trends in Big data analytics.Through data fabric architecture, organizations are able to store and retrieve an information across the distributed on-premises, cloud, and hybrid infrastructures.
- In a modern data science procedures, there are several various classifications of data, and metadata is one that informs users are about the data. A good data management strategy for a Big data requires the good metadata management from collection to archiving to processing to be cleaning. As a technologies like IoT, cloud computing, etc., advance, this will be useful in a formulating digital strategies.
- This term explains the process of running process on local system, like the system of a user, an IoT device or server, and moving that process there. A Edge computing allows the data to be processed at edge of a network, reducing number of long-distance connections are between the server and a customer, making it major trend in Big data analytics.This enhances the Data Streaming, like a real-time data streaming and processing without can causing latency; devices are respond immediately as a result. Computing at tedge is efficient because it consumes the less bandwidth and reduces organization’s development costs. It also enables the remote software to run more efficiently.
- With orchestration of a two interfaces, a cloud computing system combines the private cloud on-premises with public cloud from a third party. With the hybrid cloud deployment, processes are moved between the private and public clouds, which allows for a great flexibility and a more data deployment options. For organization to be adaptable to aspired public cloud, it needs the private cloud.This requires the building data center, which includes the servers, storage, a LAN, and load balancers. VMs and containers are must be supported by a virtualization layer or hypervisor.
- An organization’s of data service level is critical to providing a data to customers within and across the organizations. A Real-time service levels are enable end-users to interact with data in real-time or near-real-time changing Big data analytics in future scope.In addition to providing a low-cost storage to store the large quantities of raw data, data lakehouse system implements metadata layer above store in order to structure a data and improve the data management capabilities similar to data warehouse.
Top Skills You Will Gain
- Data Mining
- Machine Learning
- Data Visualization
- NoSQL Databases
- Data Warehousing
- Programming (Python, R)
- Natural Language Processing
Big Data Analytics Certification Course Key Features 100% Money Back Guarantee
5 Weeks TrainingFor Become a Expert
Certificate of TrainingFrom Industry Big Data Analytics Certification Experts
Beginner FriendlyNo Prior Knowledge Required
Build 3+ ProjectsFor Hands-on Practices
Lifetime AccessTo Self-placed Learning
Placement AssistanceTo Build Your Career
Top Companies Placement
Annual SalaryHiring Companies
Big Data Analytics Certification Course Curriculam
Experts with competence in statistics analysis, statistics technology, system learning, and artificial intelligence lead our Big Data Analytics Training running shoes. They have a collection of theoretical and practical knowledge in the Big Data era, as well as experience with various large data technologies such as Hadoop, Spark, NoSQL, and associated equipment.
The prerequisite for taking a Big Data Analytics Training is basic knowledge with concepts and tools connected with computer programming and software engineering. Knowledge of disciplines such as algorithms, statistical structures, database management systems (DBMS), and allotted computing can be beneficial.
Syllabus of Big Data Analytics Course Download syllabus
- Types of Digital Data
- Introduction to Big Data
- Apache Hadoop
- Hadoop Streaming
- Analyzing Data with Hadoop
- Hadoop Echo System
- Analyzing Data with Unix tools
- The Design of HDFS
- HDFS Concepts
- Command Line Interface
- Hadoop file system interfaces
- Data flow
- Data Ingest with Flume
- Map Reduce Framework
- Shuffle and Sort
- Map Reduce Types and Formats
- Map Reduce Features
- Techniques to optimize Map Reduce jobs
- Introduction to PIG
- Hive Shell
- HiveQL, Tables
- HBasics Concepts
- Hbase Versus RDBMS.
- Hive Metastore
- Introduction to Machine Learningr
- Supervised Learning
- Unsupervised Learning
- Collaborative Filtering
- Big Data Analytics with BigR
+91 909 279 9991
Request for Information
Analyzing Twitter Data Sets
This project could involve reading big datasets containing tweets and predicting consumer behaviors, alternatives, and interests.
Utilizing Big Data for Network Intrusion Detection
This project would contain the use of massive records units to come across intrusion attempts on a community.
Big Data Analysis and Pattern Recognition
This venture might involve gathering a extensive variety of information assets inclusive of pictures, documents, audio clips and so on.
- Mock interviews by Learnovita give you the platform to prepare, practice and experience the real-life job interview. Familiarizing yourself with the interview environment beforehand in a relaxed and stress-free environment gives you an edge over your peers.
- Our mock interviews will be conducted by industry experts with an average experience of 7+ years. So you’re sure to improve your chances of getting hired!
How Learnovita Mock Interview Works?
Request for Information
Big Data Analytics Online Training Objectives
- The Big Data Analytics certification direction is an extensive application designed to help college students expand the vital capabilities to emerge as a success statistics analysts.
- The path covers topics along with records mining techniques, programming languages, and analytics gear.
- Students will discover ways to acquire, analyze, and interpret records from numerous resources to increase meaningful visualizations and insights.
- They may even acquire the skills to construct and install predictive models and layout solutions to improve commercial enterprise choices.
- Big Data Analytics Online Training goals to offer online newcomers with the skills necessary to investigate big datasets and uncover insights by way of leveraging quantitative techniques, superior analytics strategies, software tools, and device getting to know technologies.
- It moreover affords in-depth understanding of the foundations of facts analysis, facts fashions, and statistics control.
- The schooling specializes in coaching techniques for amassing and organizing data, growing fashions and trying out algorithms which can pick out trends for enterprise experts.
- It gives a complete expertise of how data analytics can be utilized in choice making, danger management, device optimization, and more.
- Data Mining Techniques
- Machine Learning and Artificial Intelligence
- Data Visualization and Dashboarding
- Big Data Storage and Processing
- Statistic Analysis and Predictive Modelling
- In order to take the Big Data Analytics Training, you may need to have a robust foundation in programming, simple math and information, and information technology.
- You will want to be acquainted with ideas like information evaluation, statistics mining, gadget learning, and programming languages which include Python or R.
- You may want to have earlier revel in with database control and query languages. Finally, you'll want with a purpose to practice your expertise to the mission of records analysis in a realistic manner.
- Yes, there may be a want for training in Big Data Analytics.
- Big Data Analytics is a noticeably new discipline that requires specialised expertise and skills for you to be used correctly.
- By enrolling in a application or taking a course, people can benefit the necessary revel in and knowledge to recognize and analyze huge datasets to implement the maximum suitable strategies and solutions.
- Attend an online or in-individual education course. Courses along with Cloudera’s Big Data Analytics direction, IBM Big Data and Analytics Foundations, and Hortonworks Data Science and Big Data Analytics can train the fundamentals of Big Data Analytics, as well as provide arms-on enjoy with numerous lab sporting activities.
- Do on line tutorials. Numerous online sources along with Udemy, edX, Coursera, and DataCamp provide full-size tutorials on Big Data Analytics.
- Use cloud-based environments such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform to spin up Big Data Analytics labs.
- Practice with open supply software equipment inclusive of Apache Spark, Hadoop, Apache HBase and Apache Hive for statistics exploration and device gaining knowledge of.
- AI and Machine Learning- AI and machine gaining knowledge of can integrate data from multiple assets into meaningful insights. As generation keeps to strengthen, there may be extra possibilities to apply AI and machine learning to system and examine information extra successfully, allowing groups to make faster and greater informed selections.
- Data Visualization- Data visualization plays an critical role in know-how and decoding big datasets. Through statistics visualization, companies can gain treasured insights into traits and styles of their data. As the information environment evolves, so does the want for classy facts visualization techniques.
- Cloud Computing- With the growing call for for information evaluation, cloud computing has gained traction in current years. Cloud computing lets in for storing, handling, and studying huge datasets, permitting groups to carry out Big Data analytics in a value-powerful manner.
- Understand the fundamentals: First and foremost you need to benefit an expertise of the basics of big facts, such as the tools, technologies, and tactics used. Research on-line and recall taking a direction in big facts analytics to get a better information.
- Familiarize yourself with the available tools and technology: Take the time to emerge as familiar with the distinctive equipment and technology used for shooting, refining, and analyzing facts. You can regularly use open source options, including Apache Hadoop, to advantage experience inside the area.
- Master the talents: Once you have got a primary knowledge of the gear and technologies you want to end up a huge facts analytics expert, you may start gaining knowledge of the capabilities required to use them efficiently. This consists of studying the various programming languages, structures, and gear associated with huge data, consisting of SQL, Python, and R.
- Practice: Practicing is crucial. Work with and examine datasets to benefit experience in evaluating records and deriving insights.
- Data Scientists
- Business Intelligence Analysts
- Data Architects
- Data Engineers
- Machine Learning Engineers
- Data Visualization Experts
- Big Data Analytics Fundamentals
- Applied Big Data Analytics
- Machine Learning and Big Data Analytics
- SQL for Big Data Analytics
- Advanced Big Data Analytics
- Big Data Visualization and Analytics
- Big Data Processing and Analytics
Big Data Analytics Course& Certification
- A solid understanding of fundamental concepts related to data analysis, statistics, programming, and databases is often expected. Some certifications may specify required skills in particular programming languages (e.g., Python, R), data manipulation tools (e.g., SQL), and familiarity with big data technologies like Hadoop and Spark.
- Career Advancement
- Industry Recognition
- Higher Earning Potential
- Employer Preference
- Skill Enhancement
- Networking Opportunities
- Data Analyst
- Data Scientist
- Big Data Engineer
- Business Intelligence Analyst
- Machine Learning Engineer
- Certified professionals often earn higher salaries compared to non-certified individuals due to their specialized skills and recognized expertise.
- Big Data Analytics short-term certificate programs might last anywhere from a few weeks to a few months. These programs are frequently made to offer a concentrated and thorough examination of important ideas and abilities.
Pranav SrinivasSoftware Testing, Capgemini
Big Data Analytics Certification Course FAQ's
- LearnoVita will assist the job seekers to Seek, Connect & Succeed and delight the employers with the perfect candidates.
- On Successfully Completing a Career Course with LearnoVita, you Could be Eligible for Job Placement Assistance.
- 100% Placement Assistance* - We have strong relationship with over 650+ Top MNCs, When a student completes his/ her course successfully, LearnoVita Placement Cell helps him/ her interview with Major Companies like Oracle, HP, Wipro, Accenture, Google, IBM, Tech Mahindra, Amazon, CTS, TCS, HCL, Infosys, MindTree and MPhasis etc...
- LearnoVita is the Legend in offering placement to the students. Please visit our Placed Students's List on our website.
- More than 5400+ students placed in last year in India & Globally.
- LearnoVita Conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
- 85% percent placement record
- Our Placement Cell support you till you get placed in better MNC
- Please Visit Your Student's Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
- LearnoVita Certification is Accredited by all major Global Companies around the World.
- LearnoVita is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (nie) Singapore
- Also, LearnoVita Technical Experts Help's People Who Want to Clear the National Authorized Certificate in Specialized IT Domain.
- LearnoVita is offering you the most updated, relevant, and high-value real-world projects as part of the training program.
- All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.
- You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc.
- After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.
- We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities.
- View the class presentation and recordings that are available for online viewing.
- You can attend the missed session, in any other live batch.