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Tag: data analytics courses

Will Doing Big Data Analytics Courses Help To Make a Mid-Career Jump?

Posted on by Imarticus Learning

“Data is the new oil for business” is the tag line used in the modern world ruled by digitalization. Businesses today depend on data for various reasons. As you are aware data generated every day is counted in quintillion bytes so ideally, traditional methods of data handling are not sufficient to handle this lump-sum data productively.

The primary intent to learn Data Analytics is to figure out a pattern using which assessing customer preferences and tastes may be easier. Big data confines itself as a large sum of data available either in a structured or unstructured format.

Different big data analytics, tools, and techniques are on rising demand for the impact of big data on businesses. Such tools are put to effective use in finding business opportunities and making business decisions.

Competitive advantage for big data analytics aspirant with a tech background 

For a person working in a software firm who has some technical knowledge undertaking big data Hadoop course will be extremely beneficial to beat the competition. A report from Forbes suggests that the median salary for a data scientist is $110000. Corporate giants like Cisco, IBM, Oracle, Google, and Microsoft have posted numerous job openings in this field. However, Big Data has widespread use in different sectors of business like Aviation, Pharma, education, Telecom, healthcare, It, Retailing and sports. There are endless opportunities for a person who masters Big Data Analytics Courses in any phase of a career.

Merits of a private training institute

As far as private training institutes are concerned they design a comprehensive structure of big data analytics and provide hands-on training for better knowledge about the concepts. In order to make a career shift, you do not have to invest in sky-rocketing fees of legacy education institutes and their degrees. Various online private institutes offer state of the art classes, online sessions, and programs for your convenience.

Capitalize on the trending big data analytics course by opting for private online institutes who are performing extraordinarily in governing the aspiring students in any phase of their career. Learning and getting trained with professional hands may land you in a dream position.

Skilled and properly trained Big Data Analysts are paid hefty and long-term growth may be possible if you deliver the expected results to the companies.

Big data analytics training encompasses several technologies like:

  1. Machine learning which co-relates to Artificial intelligence and creates automatic proactive models that analyze bigger problems and brings about a meaningful solution.
  2. Efficient data management program to be designed by the companies for organizing the data that is constantly flowing in and out of the organization.
  3. Data mining is a technology which assesses large quantity o data to figure out a pattern which can be further called into meaningful insights for the business.
  4. In-depth understanding of Hadoop framework which skillfully stores data using commodity hardware and runs its cluster of applications in it.
  5. In-memory analytics uses system memory to analyze the data thereby saving time and better decision-making.
  6. Operating with Predictive analysis which uses historical data along with statistical tools and technologies to find a future prospect.

Some of the job titles that one may get into big data are big data engineer, data visualization expert, Hadoop developer, information architect, business managers, software testers an more.

You may be wondering why is big data being a prominent part of successful business, well, let me answer this with the following points:

  • On the long run, big data analytics tools like Hadoop and cloud analytics reduce the cost of storing a large sum of data by identifying ways to build a profitable business.
  • Big data technique Hadoop, when clubbed with memory analytics, helps in analyzing the information and make decisions immediately based on the research. Thus aids business in a fast and better decision-making process.
  • Big data analytics ability to identify the customer needs, has leveraged on the businesses to produce new products that satisfy the customer needs.

To sum up

If your previous job was mundane and not exciting enough, you could probably want to get closer to the way business works through big data analytics. Having knowledge about technical aspects will be an added advantage to take up data analytics as a mid-career jump. Explore more through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

How Can You Learn About Healthcare Data Analytics and Get Training and Certification Online?

Posted on by Imarticus Learning

The healthcare field has seen many improvements with the application of data analytics. From record-keeping, medical device calibrations, research on disease management, predictions of epidemic outbreaks, and suggestions of personalized health and treatment measures, data-analytics, ML, AI, and big data all play crucial and ever-increasing roles. Online courses are excellent as they address the pressing personnel shortage for certified data analysts and scientists. They do not make specialists of you. However, they do equip you with a generalist’s overview of the healthcare sector, update and refurbish the required skills, and offer certifications in a short period.
A paid Data Analytics courses, on the other hand, will help you hone your skills by practical learning application, effective mentoring and makes you a job-ready contributor to healthcare data analytics projects. It also serves to boost the first-timer’s confidence. During the interview rounds for your dream career and job, you will, of course, be tested on how you propose to use your skills to tackle problems that will arise and a good grasp of modeling and your industry-relevant measurable certification will go a long way.
Requisite Educational Qualifications:
Being an introductory and fundamental course, there is no necessary qualification specified. Data analysts can learn Data Analytics online and sometimes might need a basic degree with an understanding of subjects like mathematics, computer science, statistics, engineering, economics, etc. Most of these courses improve foundations and strengthen your skills. Hence, many pursue online courses at reputed institutes to give themselves the knowledge of how to apply their learning across various verticals. And truth be told, today it is all about data and no field including the healthcare sector, is free from using the same for furthering growth, efficiency, and technology.
Classroom learning during your Data Analytics Training will be needed to acquire crucial role skills including the comprehensive capture, cleaning, and organization of databases, the applications of data to business strategy, and effective communication of the analysis reports. Familiarity with excel techniques and statistics will be a plus point.
What the course teaches:
Let’s explore what most courses cover or do not cover and are moot requirements for a data analytics job-role.

A. Technical Skills:

Computer programming and CS Fundamentals including

  • Dealing with unstructured non-clinical and clinical data including blog posts, videos, reviews, social media posts, audio clips, medical images and videos that don’t fit into tables and are complex to handle.
  • SQL Coding and Databases score in operations like delete, add, query or extract functions used for transforming structures and in analytical functions when working with relational databases like patient records and insurance claims.
  • The platform of NoSQL/Hadoop is preferred with knowledge of Pig, Hive, cloud tools and so on for situations involving the transfer of data, storage, sampling, summarization, filtration, and exploration of data. Apache Spark and Scala frameworks are similar to Hadoop but much faster in handling very big-data volumes.
  • AI, MLand Neural Network knowledge and techniques are essential if you wish to score in the emerging uses of data-analytics to healthcare.
  • Data Visualization techniques that include formatting, editing, graphs, charts, etc. are easy with tools like ggplot, Matplottlib, and d3.js Tableau to make effective data forecasts, presentations and case studies.

·   Language proficiency in 

  1. R Programming.
  2. Coding in Python is recommended for versatility in its applications. Python can be used for all medical and healthcare processes and comes with a variety of libraries for nearly all verticals, browsers, etc.

B. Non-transferable Skills:
These are essentially not taught and depend on practice –

  • Quantitative and problem-solving aptitude skills
  • Grasp of inferential logic, an innovative approach, and great communicative skills
  • Above average skills in attention to detail, reporting and programming skills
  • Business acumen, team-skills, dedication, flexibility, and continued learning form a confident learner

Conclusion:
In parting, do acquire Data Analytics Training certifications online or in a paid course. Attend boot-camps, hackathons, MOOCs, etc. all of which give you support, exposure and mentorship in ML, ConvNet, and data analytics practical techniques. The demand-supply gap for data analysts ensures great payouts and undying scope over the next decade, according to the 2011 reports from Mckinsey and the survey by Accenture.

Attend and learn data analytics from a reputed institute like Imarticus Learning to emerge job-ready and with certification from day one. They stress on the non-transferable skills and personality development as well. Hurry and be an early bird!

We offer data analytics courses at our centers in Mumbai, Thane, Pune, Ahmedabad, Jaipur, Delhi, Gurgaon, Bangalore, Chennai, Hyderabad, Coimbatore.

What jobs can you get with a Data Analytics degree?

Posted on by Imarticus Learning

 

The Data Analytics industry is one of the fastest growing sectors, proving to be a job provider to thousands of potential professionals every year.

Therefore, upon the successful completion of a Data Analytics degree, there are various job options that you can explore. Some of these have been deeply detailed in the following paragraphs. Let’s have a look. 

  1. Gaining a Big Data Analytics course or degree can give you a winning career as a Business Analyst – As a Business Analyst, you will be handling responsibilities such as Database management, cleaning up of data sets and organizing them.

    Creation of data visualizations, that convey information in an engaging visual manner to the audience. You will also be responsible for building models that explain the interaction of various variables, and this will be used for companies future references. 

  2. Operations Research Analyst – An Operations Research Analyst methodically uses data mining, data modeling, data optimization, and statistical analysis to help companies, corporates and organizations run cohesively and efficiently. Their major responsibility also includes streamlining of operations processes, minimizing waste and optimizing source models. Operations Research Analysts are also called as Operations Analysts, Operations Business Analysts, and Business Operations Analysts. 

  3. Quantitative Analyst – A Quantitative Analyst usually handles the finance department using, applying and implementing trading strategies and assesses risk factors and help/guides in generating maximum profits.

    They are deeply involved in the usage and designing of mathematical models that give financial firms and organizations to price and trade securities accordingly.

    You will require skills such as a great aptitude in mathematical statistics and finances, calculus, and machine learning. These will be the basics of your career as a successful Quantitative Analyst.

  4. Market Research Analyst – Studying market trends and conditions, and observing them carefully to forecast the profitability and revenue of a certain new product or new service is a job role carried out by Market Research Analysts.

    With their skill sets, tools and techniques they research and are able to predict market trends, market downfalls, measure the precise market success of various products and services, and thus identify potential markets where the said product/service can become a future success. 

    This helps organizations, corporates, and global companies understand market trends and make a fruitful profit for themselves, while making a positive impact on the society at large, with their respective product/service. 

Through individual coaching, guidance, and mentorship, you can explore many career advantages through a valid degree course in Data Analytics. These degrees usually have strategic career partnerships with industry relevant global companies and organizations (data analytics course with placement) that will help you mold you step by step process as a Data Analyst. 

You will also gain deep practical learning through internships and first-hand exposure in a corporate set up. Networking and socializing for career connects is an important task which you will be able to do through interacting with professionals and experts during your internship.

This will then help you walk down your successful path as a Data Analysts under whatever focus/stream you may later choose to focus on. 

What are some Data Analytics Internship questions?

Posted on by Imarticus Learning

 

What do Data Analysts do?

Data analytics (DA) is the science that deals with examining raw data sets to understand the useful information they contain. This process is aided by specialized software systems. Data analysts use technologies to facilitate organizations to take business decisions in a more efficient way. The main goal is to boost the business performance of the company by improving operational efficiency and increasing the profit rates.  The positions of a business analyst, data analyst and a data scientist differ in terms of technicality. In other words, the business analysts are least technical, data analysts being more technical and the data scientists are the most technical.      

Scope and Career Prospects of Data Analytics

The scope of data analytics is progressively huge in India. Every workplace being more technology-based, there is a great demand for professionally trained data analysts, who can efficiently record and analyze data to solve business problems.  

Data analysts can work in companies that offer banking services, fraud detection jobs, telecommunications, etc. Also, they can find employment in any private technology firms and in big reputed tech companies. In India Bengaluru, hosts 27% of analytics jobs, followed by Delhi and Mumbai.

Now that you are aware of the scope of data analytics, you should join data analytics courses that offer certification and alumni.

Data Analytics Course

Why Take Up Data Analytics As a Career?

  1. Bachelor’s degree is not enough, because a specialized degree is important.
  2. The increasing demand for data analysts in today’s world. 
  3. Data analytics can be a worthwhile contribution to your profession.
  4. It is a rewarding career, you can get a higher income. 

So, take up data analytics as a career and get a great opportunity to work with renowned Multi-National Companies.   

Qualifications of Data Analyst Intern

  1. Problem-solving skills
  2. Good communication skills and analytical skills.
  3. Strong business awareness.
  4. Knowledge in SQL.
  5. Programming knowledge and application skills.
  6. Efficient in Excel.
  7. Bachelor’s degree.

7 Data Analyst internship interview questions

What is the responsibility of a data analyst?

The responsibilities of a data analyst are,

  • To resolve business-related issues for clients.
  • To analyze results and interpret data by using statistical techniques.
  • To identify new areas for improvement.
  • Filter and clean data
  • Review computer reports. 

What are the steps involved in an analytics project?

The steps involved in an analytics project are:

  • Problem defining.
  • Data exploring.
  • Data preparation.
  • Validation of data.
  • Implementation.

What is data cleansing?

Data cleaning is the process of identifying and removing errors from data in order to improve the quality of data.

What are the best tools useful for data analysis?

  • Tableau
  • RapidMiner
  • OpenRefine
  • KNIME
  • Google search operators
  • Solver
  • Wolfram Alpha’s

What can be done with suspected data or missing data?

  • A validation report should be prepared, which gives all the information about the suspected data.
  • Examine the suspicious data to determine their acceptability.
  • To work on missing data, use the best analysis strategy like deletion method, single imputation methods, etc.
  • Invalid data should be replaced with a validation code.

Explain N-gram?

An n-gram is a contiguous sequence of n items from a sequence of text or speech. It is a type of probabilistic language for predicting next item.

What is Map Reduce?

It is a framework to process large data sets, splitting them into subsets and processing each subset on a different server and blending results.

Karen’s Review of Imarticus Learning’s Post Graduate course in Big Data Analytics

Posted on by Imarticus Learning

Karen Soares, a student of Imarticus’ Post Graduate course in Big Data Analytics shares her journey from an IT graduate to an Analytics professional and a job at Peel Works.
Tell us a little about yourself.
My name is Karen Soares. I was born and brought up in Mumbai, and I graduated in B.Sc. IT, also in Mumbai. I joined Imarticus for the postgraduate program in Data Analytics. I currently work at Peel Works as a Data Analyst owing to the efforts of Imarticus Learning’s placement team.
Tell us about your experience with Imarticus.
My experience with Imarticus was really good; it was much better than I expected. I came across Imarticus by taking an online assessment on their website, and the next day I received a call from a counselor asking me to turn up for a counseling session. Initially, I was apprehensive and did not want to attend the counseling; however, the counselor persuaded me to come, and I am thankful for that. Once I arrived at Imarticus’ Mumbai office, I had an insightful session with the counselor who helped me pick the right course based on my academic and professional goals.
What has changed since you joined Imarticus Learning?
Since I joined Imarticus my life has changed drastically. I feel that I am much more confident in myself and my professional abilities. I have a complete understanding of what I do, what I work for and what I work as and that makes a lot of difference. I realized that what we learn in school and college is a bit sketchy and has barely any practical applications. But what I’ve learned at Imarticus through the practical learning approach has really stuck with me. I have a fantastic job because of Imarticus, and I enjoy going to work every day.
What do you like most about Imarticus?
The thing I like most about Imarticus is the level of comfort and approachability that they provide. Every professor here is always ready to solve your doubts and is prepared to answer all your questions – a hundred times if needed. You can never be afraid to ask seemingly silly questions, and that makes the learning experience much better. Everybody at Imarticus was accommodating throughout the course, any questions and queries were always answered at the earliest, and that’s what makes an excellent institute.
Are you on the right track to achieve your Analytics aspirations? Click Here and speak to a career counselor today!

The Next Big Thing in Data Analytics

Posted on by Imarticus Learning

 

Data analytics is fast evolving, and with the increasing use of streaming data, machine data and big data only adds to the continuous challenges encountered during analyzing log data, enterprise application data, web information, historical data stored in documents and reports etc.

In the present day, data analyst struggle to provide a solution for business and client request. As it is, there is a substantial deficient of talent in the field of business data analysts and data scientist, with businesses continue to struggle with data reconciliation, data blending, data access, development of data analytics tools and data mining techniques.

Data analyst and data scientist are frequently unable to discover data and information required and are often unaware of the latest data analytics tools such as the self-service data prep tools assist in the improvement of productivity. Furthermore, the continuous development of advanced social technologies and with the incorporation of various social features have caused an increased expectation regarding timeliness and information availability. Similarly, users have similar enhanced expectations towards business information irrespective of where the data originates or how is it formatted. There is an increasing demand for instant access for data and the ease of sharing it with essential stakeholders.

 

Data socialization is the metamorphosis of data mining techniques to enhance data accessibility across companies, teams, and individuals. Data socialization is changing how business think about business data and how employees interface with business data.

Data socialization comprise of management of data platform which enables the linkage between self-service visual data preparation, automation, cataloging, data discovery and governance features with essential features common to a various social media platform. Hereby, it provides businesses with the ability to leverage social media metrics such as user ratings, discussions, recommendations, comments etc. to enable usage of data for improved decision making.

What is Data Socialisation?

It is a data analytic tool which enables business analyst, data scientist and various relevant users throughout an organization to search, reuse, and share managed data. It aids in the achievement of agility and enterprise collaboration. Data socialization allows employees to find and utilize data which is accessible to them within a specified data ecosystem and assist in the creation of a social network of raw data sets which are curated and certified. These data ecosystems have various levels of controls, restrictions, and limitations which can be well defined for each individual person in an organization. These data mining techniques aid the strengthening an environment of data access, wherein analyst and users are allowed to learn from one another, enhance productivity and be well-connected as its sources, cleans and prepares of data analytics.

Some Characteristics of Data Socialisation

Some of the critical characteristics of data socialization include:

  • The ability of understanding data with regards to its relevance about how a particular data is deemed to be used by various users within an enterprise.
  • Involvement of collaboration of essential users with the data set to harness knowledge which often remains unshared.
  • It enables enterprise users to search for data which has been cataloged, prepare data models, and index metadata by users, type, application, and various unique parameters.
  • Data Socialisation enables to perform a data quality score, suggest for relevant data sources, automatically recommend actions for preparing actions designed according to user persona.

With various business applications incorporating features of social media functions towards improvement in business collaboration, at this moment making individuals and companies well informed, productive and agile.

Data socialization aids in delivering various benefits to various data analytics tools and removal of obstacles towards accessing and sharing data, at this moment allowing data scientist, business users and business information analyst in improving their productivity and decision-making. It further empowers analyst, data scientist and other business users across various departments to collaborate using the available data. By providing the right person with the correct data required to make informed, educated and timely decisions, the implementation of Data socialization is deemed to be the next big thing in data analytics.

Join Big Data Analytics Course from Imarticus Learning to start your career in data analytics. 

15 Terms Everyone in the R Programming Industry Should Know

Posted on by Imarticus Learning

 
Of late, the R language has gained popularity in the technology circles. R language is counted among the open source program, which is maintained by R –Core development team. This team comprises of developers all across the world who work voluntarily.
This language is used to carry out many statistical operations, while it is a common line driven program. It was developed by John Chambers and his team at Bell Labs in the US for implementing S programming language. There are several benefits of using this language, which give people from different industries a reason to adopt it. It is among the best machine learning and data analysis language. 
People making a career in the domain of data analytics course can find good R programming opportunities. If you are new in this field and want to learn and master, have a look at the list of 15 Terms everyone in the R Programming Industry Should Know, have a look:
1). Mean in R – The mean in R is the average of the total numbers, which are calculated with the central value of a set of numbers. For calculating this number, you simply have to add all the numbers together and then divide by the available numbers found there.
2). The compiler in R– It is something that helps in transforming the computer code, which is written in one programming language (to be precise the source language) into the other compiler language, which is the target language.
3). Median in R – It is a center of the sorted out list of numbers, however, if the numbers of even, things are different to some extent. In the case of the R language, first, you have to find out the middle pair of numbers followed by finding out the value of the midway number. The numbers are added and then divided by two to get the same.
4). Variance in R – It is basically the average of squared difference that is found from the Mean.
5). A polynomial in R – If you break this terminology you will get the meaning. Poly is many and nominal is a term, which means many terms.
6). Element Recycling – The vectors of diverse lengths when coming together in any operation then shorter vector elements are reused for completing the operation. This is known as element recycling.
7). Factor variable – These are categorical variables, which hold the string or numeric values. These are used in different kinds of graphics and particularly for statistical modeling wherein numerous degrees of freedom is allocated.
8). Data frame in R – These have diverse inputs in the form of integers, characters, etc.
9). The matrix in R – These have homogenous data types that are stored including similar kinds of integers and characters.
10). Function in R – Most of the functions in this language are the functions of functions. The objects in function fall under the local to a function, while these are returned to any kind of data type.
11). Attribute function in R – This function has an attribute of carrying out two different functions together. These include both the object and the attribute’s name.
12). The length function in R – This is the function that helps in getting or setting the right length of the vector/object.
13). Data Structure in R – It is a special kind of format that helps in storing and organizing data. These include file, array, and record found in the table and tree. 
14). File in R – It is a file extension for any script written in R language, which is designed for graphical and statistical purposes.
15). Arbitrary function in R – It is any function in a program; however, it is often referred usually to the same category of function that people deal with it.
Conclusion
There are many more things to learn and know about the R Language before you think about the R programming opportunities. The above is the modest list of terms found in R Language.

Future of Big Data Hadoop Developer in India

Posted on by Imarticus Learning

In this era of electronic and digital devices, most people are using Big Data, ML, AI and such without really understanding what goes on to provide those services. Data is at the very center of any application and the sheer volumes of data generated, the variety of sources and formats, the need to manage, clean, prepare and draw inferences for business purposes and making decisions is being used extremely widely. And this spawning of data, means the projects involve Big Data and that technology has to evolve and changes to manage it. This also indirectly implies the need for Hadoop developers. The relationships are symbiotic and spur growth in each other’s needs.

Why Choose Big Data Hadoop As a Career

• Since data is an asset people trained on handling the large amounts of data performing analytics on it and providing the right gainful assets for business decisions are also fast being considered invaluable assets.
• Those employees who do not re-skill to include managing Big Data face the risks of getting laid off. For example, TCS, Infosys, and many other data giants laid off nearly 56,000 people in just one year.
• 77% of the companies and verticals across industries are adapting to use Big Data. Thus many are recruiting data analysts and scientists. Even the non-IT sector!
• The payouts are second to none in the category and a large number of aspirants are taking up formal Hadoop careers, both newbies and those changing careers mid-way.
• Data is growing and will continue to be used even in the smallest of devices and applications creating a demand of personnel to handle Big Data.

The Hadoop Career Choice

Pros:
• Big data applications and demand for trained personnel shows tremendous growth.
• Job scope is unending since data continues to grow exponentially and is used by most devices today.
• Among the best technology for managing Big Data sets Hadoop scores as the most popular suite.
• The salaries and payouts globally are better than for other jobs.
• Most verticals and industries, a whopping 77%, are switching tracks to use Big Data.
• Hadoop is excellent at handling petabytes of Big Data.
Cons:
• Your skills need to be of practical nature and constantly updated to keep pace with evolving technology.
• You need a combination of skills that may require formal training and is hard to assimilate on your own before you land the job.

How to Land that Dream job

Today it would be exceptional if a company does not use Hadoop and data analytics in one form or the other. Among the ones that you can easily recollect are New York Times, Amazon, Facebook, eBay, Google, IBM, LinkedIn, Spotify, Yahoo!, Twitter and many more. Big Data, Data Analytics, and Deep Learning are widely applied to build neural networks in almost all data-intensive industries. However, not all are blessed with being able to learn, update knowledge and be practically adept with the Hadoop platform which requires a comprehensive ML knowledge, AI deep learning, data handling, statistical modeling and visualization techniques among other skills.
One can do separate modules or certificate Big-Data Hadoop training courses with Imarticus Learning who provide such learning as short-term courses, MOOCs, online classrooms, regular classrooms, and even one-on-one courses. Choices are aplenty with materials, tutorials and options for training being readily available thanks to high-speed data and visualization made possible by the internet.
Doing a formal Hadoop training course with certification from a reputed institute like Imarticus Learning helps because: 
• Their certifications are widely recognized and accepted by employers.
• They provide comprehensive learning experiences including the latest best practices, an updated curriculum, and the latest training platforms.
• Employers use the credential to measure your practical skills attained and assess you are job-prepared.
• It adds to your resume and opens the doors to the new career.
• Knowledge in Big Data is best imbibed through hands-on practice in real-world situations and rote knowledge gained of concepts may not be entirely useful.
The best courses for Big data Hadoop and Advanced Analytics are available at the IIMs at Lucknow, Calcutta, and Bangalore at the IITs of Delhi and Bombay. This is an apt course for people with lower experience levels since their curriculum covers a gamut of relevant topics in-depth with sufficient time to enable you to assimilate the concepts.
The Big data training courses run by software training institutes like Imarticus are also excellent programs which cost more but focus on training you, with the latest software and inculcating practical expertise. Face-to-face lab sessions, mandatory project work, use of role-plays, interactive tutoring and access to the best resources are also very advantageous to you when making the switch.
Job Scope and Salary Offered:
Persons with up to 4 years experience can expect salaries in the range of 10-12 lakhs pa at the MNCs according to the Analytics India Magazine. Yes, the demand for jobs in this sector will never die down and is presently facing an acute shortage.
Hadoop Course Learning:
You can use online resources and do it yourself using top10online courses.com. However, formal training has many advantages and is recommended. Join the Hadoop course at a reputed institute like Imarticus Learning.
Hadoop has a vast array of subsystems which are hard to learn for the beginner without formal training. The course helps you assimilate the ecosystem and apply these systems to solving real-world industry-related problems in real-time through assignments, quizzes, practical classes and of course do some small projects to show off your newly acquired skills. The best part is that you have certified trainers leading convenient modes and batches to help you along even if you are already working.
The steps that follow are the Hadoop progressive tutorial in brief.
• Hadoop for desktop installation using the Ambari UI and HortonWorks.
• Choose a cluster to manage with MapReduce and HDFS.
• Use Spark, Pig etc to write simple data analysis programs.
• Work on querying your database with programs like Hive, Sqoop, Presto, MySQL, Cassandra, HBase, MongoDB, and Phoenix.
• Work the ecosystem of Hadoop for designing applications that are industry-relevant.
• Use Hue, Mesos, Oozie, YARN, Zookeeper, and Zeppelin to manage your cluster.
• Practice data streaming with real-time applications in Storm, Kafka, Spark, Flume, and Flink.
• Start building your project portfolio and get on GitHub.
Conclusion:
In parting, India and the bigger cities like Bangalore, Hyderabad, and Mumbai are seeing massive growth in the need for Hadoop developers. You will also benefit from a Hadoop training course in Data Analytics and it is worth it when your certification helps you land the dream career you want. So don’t wait. Take that leap into Hadoop today!

What are The Different Fields in Data Analytics?

Posted on by Imarticus Learning

One of the most popular technology-empowered jobs out there, data analytics consists of various disciplines in the field of data science. There are plenty of different areas in which data analytics is applied, with the banking sector being the foremost. As the world starts adopting data analytics techniques, there are different jobs that are present in the field of data analytics.

Here are four of the main fields in the data analytics sector:
1.Data analyst:
Some companies use the terms “data scientist” and “data analyst” interchangeably. Data analysts generally work with SQL databases and pull data out of the same. The job also entails becoming a master of Tableau and Excel and occasionally analyze results of A/B testing and leading the Google Analytics account. Other roles can also include reporting dashboard data and producing data visualizations.
2.Data Engineer:
Data engineers are generally bought in when companies start getting a lot of traffic and need someone to set up the infrastructure to move forward. There’s also a need for somebody to provide constant analysis and this job can generally be posted under “Data Scientists” or “Data Engineers” as well.
Data engineers require a decent knowledge of machine learning, and heavy statistics as these are one of the main assets companies look for when they’re starting out themselves. Software engineering skills are seen as more of a secondary requirement during the initial phase. Data engineers generally get to own all their work but won’t have much guidance and could reach a point of stagnation.
3.Machine Learning Engineer:
There are many companies where data ends up being their main product. Data analysts or machine learning will be a huge part of their internal processes here. A machine learning engineer who has an education in statistics, physics or mathematics will have a bigger role in these situations. If they’re looking at continuing in an academic path even afterward, then this is a great role to fulfill.
Most companies which look out for machine learning engineers are consumer-facing and have huge data which they offer out to other companies.
4.Data science generalist:
Companies look for data science generalists to join other data scientists internally. Companies that take interview care about data but aren’t necessarily a data company themselves. They will be on the lookout for individuals who can work on a wide variety of hats, including touch production code, analysis, data visualization and more.
Data science generalists are sought after to fulfill any specific niche which a company feels their team lacks. This can include areas such as machine learning or data visualization for example.
Thus, it’s important that you’re always on the lookout for a job that satisfied your skill set the best. There are so many options available for those interested, and with data analytics shaping the world we live in, it will serve you well if you can find your own niche.
Join Imarticus to get the best in big data analytics courses and fast forward your career graph in the field of data science. We offer data analytics at our centers in Thane, Pune, Bangalore, Chennai, Hyderabad, Coimbatore, Delhi.

Should You Start With Big Data Training or Learn Data Analytics? Which One to Start First?

Posted on by Imarticus Learning

 
It is always a better choice to learn Big data training rather than generalize with data-analytics which is a very large field. Today’s world deals with not just Big Data but the term for big have increased by many multiples of big in terms of data volume. Further, the tools that are used are fast evolving and learning the Big-Data tools first can be done online and through courses. Once you have proficiency in dealing with big data you can also do data analytics courses and understand better the concepts of analytics while applying them to databases classified as big and very, very big!

Difference Between Data Analytics And Big Data

The languages and tools used and the end purpose is different in the two courses one being used in managing large database sets while the other focuses on gaining and providing insights from such datasets. Data science covers courses to learn how to visualize data, make predictive models using R/Python and then use manipulation techniques on the data to get foresight and forecasts or trends. Big Data courses are about managing the data systems and databases. Tools used in Big data training are Hadoop, Tableau, R, NoSQL, and many others that deal with managing the data and integrating the results to give the desired dashboards, visualizations, graphics and summary of statistics.
The R language is taught in data sciences and includes R as its programming language because of its tool range to deal with statistical and analytical applications. The applications used need R programming and hence R developers would be more preferred. Big data training on the other hand, uses MapReduce for Java-based installation programs, needs to integrate and connect with R through Tableau from the Hadoop library and uses data processing tools like Flume, Hive, Sqoop, HBase etc
Learning Hadoop Course
You can use online resources and do it yourself using top10online courses.com. However, formal training has many advantages and is highly recommended. Join the Big data training Hadoop course at a reputed institute like Imarticus Learning. Hadoop has a vast array of subsystems which are hard to learn for the beginner without formal training. The course helps you assimilate the ecosystem and apply these systems to solving real-world industry-related problems in real-time through assignments, quizzes, practical classes and of course do some small projects to show off your newly acquired skills. The best part is that you have certified trainers leading convenient modes and batches to help you along even if you are already working.
Start building your project portfolio and get on GitHub.
The steps that follow are the Hadoop progressive tutorial in brief.
• Hadoop for desktop installation using the Ambari UI and HortonWorks.
• Choose a cluster to manage with MapReduce and HDFS.
• Use Spark, Pig etc to write simple data analysis programs.
• Work on querying your database with programs like Hive, Sqoop, Presto, MySQL, Cassandra, HBase, MongoDB, and Phoenix.
• Work the ecosystem of Hadoop for designing applications that are industry-relevant.
• Use to manage your cluster with Hue, Mesos, Oozie, YARN, Zookeeper, and Zeppelin.
• Practice data streaming with real-time applications in Storm, Kafka, Spark, Flume, and Flink.

Why do a data analytics course?

Today it would be exceptional if a company does not use Hadoop and data analytics in one form or the other. Among the ones that you can easily recollect are New York Times, Amazon, Facebook, eBay, Google, IBM, LinkedIn, Spotify, Yahoo!, Twitter and many more. Big Data, Data Analytics and Deep Learning are widely applied to build neural networks in almost all data-intensive industries.
However, not all are blessed with being able to learn, update knowledge and be practically adept with the Big data training Hadoop platform which requires a comprehensive ML knowledge, AI deep learning, data handling, statistical modelling and visualization techniques among other skills. One can do separate modules or certificate Big-Data Hadoop training courses with Imarticus Learning who offer such learning as short-term courses, MOOCs, online classrooms, regular classrooms, and even one-on-one courses. Choices are aplenty with materials, tutorials and options for training being readily available thanks to high-speed data and visualization made possible by the internet.
Doing a formal data analytics training course with certification from a reputed institute like Imarticus Learning helps because
• Their certifications are widely recognized and accepted by employers.
• They provide comprehensive learning experiences including the latest best practices, an updated curriculum and the latest training platforms.
• Employers use the credential to measure your practical skills attained and assess you are job-prepared.
• It’s a feather in your hat that adds to your resume and opens doors to the new career.
• Knowledge in Analytics is best imbibed through hands-on practice in real-world situations and rote knowledge gained of concepts may not be entirely useful.
The best Big data training courses for Advanced Analytics are available at the IIMs at Lucknow, Calcutta, and Bangalore or at the IITs of Delhi and Bombay. This is an apt course for people with lower experience levels since their curriculum covers a gamut of relevant topics in depth with sufficient time to enable you to assimilate the concepts.
The courses run by software training institutes like Imarticus are also excellent programs which cost more but focus on training you with the latest software and inculcating practical expertise. Very experienced professionals are likely to get corporate sponsorship and can avail training at competitive discounted rates. Face-to-face lab sessions, mandatory project work, use of role-plays, interactive tutoring and access to the best resources are also very advantageous to you when making the switch.
Job scope and salary offered:
Persons with up to 4 years experience can expect salaries in the range of 10-12 lakhs pa at the MNCs according to the Analytics India Magazine. Yes, the demand for jobs in this sector will never die down and is presently facing an acute shortage.
Conclusion:
In parting, there are plenty of options that you can research more on. It is worth it when your Big data training certification helps you land the dream career you want immaterial of the route you followed. Whether you prefer managing databases and then getting at the insights or choose to get the insights and then learn how to train and manage the datasets is your choice. Both choices will be in demand for jobs over the next decade. So don’t wait. Take that leap into data today!