In order to become an efficient developer of Hadoop technology, the course on Hadoop and Big data will provide expanded understanding and techniques. Besides learning, the virtual realization of live industry applications by employing the main concepts of the subject. Large data groups can be maintained in simpler versions for easy accessibility and management with simple programming modules. Hadoop training is handled by technology with the highest skills.
Additional Info
A massive amount of data may be brought together and analyzed using Big Data platforms to uncover patterns that will help the organization expand, enhance productivity, and add value to its products and services . Hadoop is the most widely used of these systems. Hadoop is capable of analyzing and extracting usable information from large amounts of data quickly.
Hadoop is a software tool that employs a network of several computers to solve problems involving enormous volumes of computation and data, both structured and unstructured, allowing for greater flexibility in data collecting, processing, analysis, and management. It has an open-source distributed framework for distributing Big data application storage, management, and processing over scalable clusters of computer systems.
Roles and responsibilities of a Big Data Administrator :
- Construct, install, and configure a Hadoop cluster
- Configure and install software
- Manage the overall health and well-being of the Hadoop cluster
- Access provided and managed
- Assist with the design and implementation of physical and online security systems
- Work with Hadoop Architect on storage and database structure design and configuration
Roles and responsibilities of a Big Data Architect :
- Create a concept, a plan, and a design. Design functional and technological architectures for the Hadoop data system
- Complete understanding of big data ecosystem technologies and their applications
- Technology selection and analysis of the framework and technical requirements
- On the Hadoop/big data platform, manage all databases, their objects, and data
- Collaboration between Hadoop Administrators, Hadoop Architects, and Hadoop Developers is essential
- Practical experience with Hadoop's core tools and technologies
- Implement and manage big data solutions
- Manage the entire Hadoop/big data solution
Job Duties and Responsibilities of a Big Data Analyst
- Analyze data and place it in the context of company functions and demands
- Data and business functions are well-understood
- Adept at analyzing data on the fly
- Serve as a link between IT and the business world
Job Duties and Responsibilities of a Big Data Developer :
- Using open-source programming languages, create custom apps for the Hadoop platform
- Stakeholders are informed about design concepts
- Develop an ETL/ELT procedure to locate the correct data in a readable manner
- Recognize data sources, data structures, and their relationships
- Exceptional analytic and logical abilities
Job Roles and Responsibilities for Data Visualization Developers :
- Develop a data visualization analysis to give decision-makers value-added analytics
- Understand the data structure and data flow between systems to ensure that the appropriate data is available for reporting and analytics
- To ensure data integrity and completeness, collaborate closely with data quality and analysts
Job Duties and Responsibilities of a Big Data Scientist :
- Modeling and development for predictive analytics
- Analyze complex and heterogeneous data to assist a company in making decisions
- Software engineer with good math and statistics skills; applied scientist by nature
Job Roles and Responsibilities of a Big Data Steward :
- Allow the company to spend less time looking for data and more time putting it to good use
- Implement and ensure data quality with the support of the necessary people, procedures, and technologies, and foster an analytic culture throughout the organization
- Define and implement data-related policies, auditing, and laws; collaborate with multiple IT and business departments to establish data provisioning and sharing procedures
- Determine and implement the appropriate master data and metadata management policies
- Ascertain that all security and operational measures are in place to protect the company's data platform
Roles and responsibilities of Hadoop :
Developer for Hadoop :
The actual coding or programming of Hadoop applications is the responsibility of a Hadoop Developer. This position is comparable to that of a Software Developer. The job functions are nearly identical. However, the former falls within the Big Data umbrella.
- Development and implementation of Hadoop
- Hive and Pig for pre-processing
- Creating, constructing, installing, configuring, and maintaining Hadoop
- Analyze large data sets to discover new information.
- Create data tracking web services that are scalable and high-performing.
- HBase administration and deployment
- Prototypes are tested and handed over to operational teams.
Architect of Hadoop :
Big Data Architect creates high-performance, low-cost Big Data applications to assist clients in answering their business concerns. There is a lot of information. Being nimble is also advantageous, especially when dealing with modern technology. You choose tools carefully able to embrace open-source technologies in all of their positive and negative elementsYou should choose tools carefully and embrace open-source technologies in all of their benefits and drawbacks.
- Take ownership of the Hadoop Life Cycle in the enterprise and serve as a liaison between data scientists, engineers, demands of the organization.
- Perform a thorough analysis of the requirements and select the work platform solely for this purpose.
- It required that you have a thorough understanding of Hadoop Architecture and HDFS.
- MapReduce, HBase, Pig, Java, and Hive are all skills that are useful to have.
- Assure that the Hadoop solution chosen deployed successfully.
Required Skills for Big Data and Hadoop :
- Skills in Analyze
- Ability to Visualize Data
- Knowledge of the business domain and Big Data tools are required
- Problem-solving skills are a necessary part of programming
- Data mining skills using SQL (Structured Query Language)
- Technology acquaintance
- Knowledge of Public, Private, and Hybrid Clouds
- The hands-on experience has taught me a lot of skills
- Expertise in Hadoop HDFS, Hive, Pig, Flume, and Sqoop.
- Working in HQL is a plus.
- Pig Latin and Map Writing Experience
- Reduce the number of jobs
- Hadoop fundamentals are well-understood.
- Understanding of data loading technologies such as Flume, Sqoop, and others Analytical and problem-solving skills; application of these talents in the Big Data area
- Database principles, methods, architecture, and theories are well-understood.
Tools for Big Data :
- Hadoop
- Spark
- Flink Apache
- Storm Apache
- Cassandra Apache
- HDFS
- HIVE
- NoSQL
- Mahout
- Avro
- GIS tools
- Flume
- Clouds
- Spark
- MapReduce
- Impala
Integration Module :
The use of software, services, and business processes for extracting data from various sources to make coherent and meaningful information is data integration. Data integration makes data analysis faster and more efficient. Big data integration tools are essential because they become more accessible to sort via large amounts of structured or unstructured data. Software, hardware, service, and business practices may include data integration tools. Integration platforms contribute to a unified and centralized system and business unit data management across a company. Big data cloud tools and services link data, applications, APIs, things, and other sources over the device
Certifications :
- Professional Cloudera Certified
- Big Data certification Intellipaat Hadoop
- MCSE of Microsoft : Analysis and Data Management
- Certification of Hortonworks Hadoop
- The Developer Exam certified by MongoDB
- EMC data science and data analysis certification
- Data Scientist SAS Certified
- US Data Science Council Certification
- Certification for Oracle Business Intelligence
- Massive Data Sets Certificate for Mining
- Certification for Hadoop MapR
- Hadoop Certification from IBM
- SAS Certification for Hadoop
Benefits of Big data :
Everybody heard of Big Data and the wave in the industry which created. After all, there is always news: companies from different industries use big data to promote decision-making on data. The popularity of Big Data is now widening beyond the technology sector to include, among others: health, training, government, retail, production, BFSI, and supply chain management and logistics. Nearly every company and business, large or small, already harnesses the advantages of big data.
"Big data are high-volume, high-speed, and diversified information assets that require new processing methods to enable enhanced decision-making," Gartner said, Rapid development and implementation of disruptive technology leading to the rapidly increasing mobile data transmission, cloud computing, and high smartphone penetration all contribute to the increasing volume and complexity of large data sets,Because the benefits of Big Data are numerous, companies are quick to take advantage of Big data technologies.
Lowering Costs :
- Maintain and manage your internet reputation
- Identify points that are hidden in large data sets to influence business decisions.
- Risks are mitigated quickly through the optimization of complex decisions for unexpected events and potential threats.
- Identify problems in real-time in systems and business processes.
- Unlock the real marketing potential based on data.
- Check the data of customers for custom products, services, offers, discounts, etc.
- Assist in the timely delivery of products and services that meet and exceed client expectations.
- Diversify revenue streams to increase revenues and return on investment.
- Respond in real-time to client requests, complaints, and questions.
- Encourage innovative company tactics, products, and services to emerge.
Benefits of Hadoop :
- Excellent value for money
- Excellent data consistency
- Scalable to the max
- Simple, quick, and adaptable
- Authentication and security that is comprehensive
Payscale for BigData :
Companies pay Big data experts between 200K and 350K per hour on average. A Data Analyst earns an average of 614K a year. In India, a Hadoop developer earns an average of $965K a year.
