This Big Data and Hadoop training course in ACTE, will make you learn the ways of storing data that allow for efficient processing and analysis. You will also gain the skills you need to store, manage, process and analyse massive amounts of unstructured data to create an appropriate data lake. Get introduced to leading products such as Hadoop to learn how to apply Big Data in the real world. Start Learning with us ACTE Hadoop Classroom & Online Training Course.
Hadoop skills are in demand – this is an undeniable fact! Hence, there is an urgent need for IT professionals to keep themselves in trend with Hadoop and Big Data technologies. Apache Hadoop provides you with means to ramp up your career and gives you the following advantages: Accelerated career growth.
Hadoop is the supermodel of Big Data. If you are a Fresher there is a huge scope if you are skilled in Hadoop. The need for analytics professionals and Big Data architects is also increasing . Today many people are looking to pursue their big data career by grabbing big data jobs as freshers.
Even as a fresher, you can get a job in Hadoop domain. It is definitely not impossible for anyone to land a job in the Hadoop domain if they invest their mind in preparing and putting their best effort in learning and understanding the Hadoop concepts.
We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings for Hadoop. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.
A Hadoop Cluster uses Master-Slave architecture. It consist of a Single Master (NameNode) and a Cluster of Slaves (DataNodes) to store and process data. Hadoop is designed to run on a large number of machines that do not share any memory or disks. These DataNodes are configured as Cluster using Hadoop Configuration files. Hadoop uses a concept of replication to ensure that at least one copy of data is available in the cluster all the time. Because there are multiple copy of data, data stored on a server that goes offline or dies can be automatically replicated from a known good copy.
- To learn Hadoop and build an excellent career in Hadoop, having basic knowledge of Linux and knowing the basic programming principles of Java is a must. Thus, to incredibly excel in the entrenched technology of Apache Hadoop, it is recommended that you at least learn Java basics.
- Learning Hadoop is not an easy task but it becomes hassle-free if students know about the hurdles overpowering it. One of the most frequently asked questions by prospective Hadoopers is- “How much java is required for hadoop”? Hadoop is an open source software built on Java thus making it necessary for every Hadooper to be well-versed with at least java essentials for hadoop. Having knowledge of advanced Java concepts for hadoop is a plus but definitely not compulsory to learn hadoop. Your search for the question “How much Java is required for Hadoop?” ends here as this article explains elaborately on java essentials for Hadoop.
Apache Hadoop is an open source platform built on two technologies Linux operating system and Java programming language. Java is used for storing, analysing and processing large data sets. ... Hadoop is Java-based, so it typically requires professionals to learn Java for Hadoop.
Yes, you can learn Hadoop, without any basic programming knowledge . The only one thing matters is your dedication towards your work. If you really want to learn something, then you can easily learn. It also depends upon on which profile you want to start your work like there are various fields in Hadoop.
Our course ware is designed to give a hands-on approach to the students in Hadoop. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
Yes It is worth , Future will be bright. Learning Hadoop will definitely give you a basic understanding about working of other options as well. Moreover, several organizations are using Hadoop for their workload. So there are lot of opportunities for good developers in this domain. Indeed it is!
No Learning Hadoop is not very difficult. Hadoop is a framework of java. Java is not a compulsory prerequisite for learning hadoop. ... Hadoop is an open source software platform for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware.
Hadoop framework can be coded in any language, but still, Java is preferred. For Hadoop, the knowledge of Core Java is sufficient, and it will take approximately 5-9 months. Learning Linux operating system: - It is recommended to have a basic understanding and working of the Linux operating system.
Hadoop brings in better career opportunities in 2015.
Learn Hadoop to pace up with the exponentially growing Big Data Market.
Increased Number of Hadoop Jobs.
Learn Hadoop to pace up with the increased adoption of Hadoop by Big data companies.
Differences Between Business Intelligence And Big Data
Business Intelligence in simple terms is the collection of systems, software, and products, which can import large data streams and use them to generate meaningful information that point towards the specific use-case or scenario.
Big data is the most buzzing word in the business. Big Data is changing our day to day business life. Everybody thinks that Big Data is nothing but a massive amount of data. But in reality it’s not a just massive amount of data, it is also about the structure of the data, processing the data with the purpose of delivering added value to the organization.
Key Differences Between Business Intelligence and Big Data
Below is the list of items, explain the differences between the Business Intelligence and Big Data
- Both BI and Big data goal is to help the business to make good decisions by analyzing the huge datasets to expand the business and optimizing the cost.
- This data analysis not only enables decision making but also involves an active part in the development of strategies and methods that make sure the success of organizations. This data analysis can be called “Business Intelligence”, whereas “Big Data” is a relatively new term for Business intelligence.
- Since the times of BI, the volumes of data sets become incredibly large, the best example we can consider is social media. As the result, more effort and strategies should be applied to tackle with them and make them useful for successful business.
- Business Intelligence helps in finding the answers to the business questions we know, whereas Big Data helps us in finding the questions and answers that we didn’t know before.
- Although Business Intelligence and Big Data are two technologies used to analyze data sets to helps organizations in the decision-making process, there is differences present between them. They both differ in the way they analyze the data.
- Business Intelligence is based on the principle of combining all business data sets into a central server, this data will be analyzed in offline mode, after saving the information in a platform or environment called Data Warehouse. The data sets are structured in a relational database with additional indexes and forms of access to the tables in the warehouse.
- Whereas in the Big Data environment, data is stored on a distributed file system (e.g. HDFS), rather than storing on a central server. Data will be distributed across the worker nodes for easy processing. Distributed File System is much safer and flexible.
- BI solutions carry the data to the processing functions, whereas Big Data solutions take the processing functions to the data sets. Since the analysis is positioned around the information (Data), it is simpler to handler lager amounts.
- BI solutions are more towards the structured data, whereas Big Data tools can process and analyze data in different formats, both structured and unstructured.
- Big Data solutions can process the historical data and also data coming from real-time sources, whereas in Business Intelligence, it processes the historical data sets.
- Big Data technology uses parallel processing concepts (Map reducing algorithm), which improves the speed of analyzing and processing the data sets by distributing jobs into several parallel execution processes, at the end the results are combined and shown, this makes analyzing the large volumes easier.
Business Intelligence vs Big Data Comparison Table
Purpose - The purpose of Business Intelligence is to help the business to make better decisions. Business Intelligence helps in delivering accurate reports by extracting information directly from the data source. The main purpose of Big Data is to capture, process, and analyze the data, both structured and unstructured to improve customer outcomes.
EcoSystem / Components - In Business Intelligence operation systems, ERP databases, Data Warehouse, Dashboard etc. As well as in Big Data Hadoop, Spark, R Server, hive, HDFS etc.
Benefits
Below is the list of benefits of Business Intelligence
- Helps in making better business decisions
- Faster and more accurate reporting and analysis
- Improved data quality
- Reduced costs
- Increase revenues
- Improved operational efficiency etc.
Below is the list of benefits of Big Data
- Better Decision making
- Fraud detection
- Storage, mining, and analysis of data
- Market prediction &and forecasting
- Improves the service
- Helps in implementing the new strategies
- Keep up with customer trends
- Cost savings
- Better sales insights, which helps in increasing revenues etc.