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.
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Tag: big data analytics
Future of Big Data Hadoop Developer in India
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!
Data Lake And Big Data Analytics
If you have been in the IT space and data analytics space for some time now, you might have come across the term Data Lake at least once. But since the technology is in its early days, not a lot of people known what it is all about and thus in this article we will discuss all about data lakes, their benefits and how they are helping in data analytics.
What is a Data Lake?
In the most simplest of terms, a data lake is a centralized storage or repository that allows you to store all your structured and unstructured data, be it of any scale. The main significant difference between a data lake and other centralized repository options available in the market is the fact that a data lake will allow you to store your data without the need of any restructuring and also allows you to run various kinds of data analytics right on the repository.
The various data analytics option present in a data lake starts from dashboards and goes all the way up to visualisations and big data processing, and even real-time analytics and machine learning to help the user for making better decisions.
The Need For A Data Lake
As you might have already guessed, the need for access to a data lake is more important in this day and age than ever before, since the number of companies dealing with big data is constantly on the rise. A recent survey, conducted by Aberdeen found that companies which used data lake facilities were able to perform 9 per cent better to those who didn’t; this fact alone can contribute to the need of using a data lake.
The Benefits of a Data Lake
Similar to any other technology in the market, Data Lake too comes with a host of advantages which helps it stand apart from the rest. Some of the most significant ones are as mentioned below.
- Capability to store and run analytics, thus deriving results from unlimited data sources
- Capability to store all types of data, both structured and unstructured, thus covering everything from social media posts to CRM data
- Increased flexibility from other systems in the market
- Option to eliminate data silos
- Ability to run unlimited queries at any point in time
Data Lake and Data Analytics
As mentioned in the earlier paragraphs, data lakes in today’s world have multitude applications, one of the most significant being the ability to run data analytics on a host of different data types.
Companies which deal with a massive amount of big data, often face with the difficulty of storing different formats at different locations, thus making data analytics a virtually impossible option. But with data lakes, all forms of data, both structured and unstructured can be stored in one place, thus allowing the user to run analytics and visualization from one dashboard and derive results. On top of that, having a single data lake, companies save up on huge amounts of money and make higher profits in the long run.
Importance of Data Analysis in India
The importance of data in the world of today can not overstate. Though data has formed the backbone of all research for centuries, today, its use has spread to businesses – both online and offline, governments, think tanks which help in policy formulation, and professionals.
With the surge is collection and dissemination of data, the importance of data analysis has grown as well. While data collation is vital, it is just the first step in the process of using it. The ultimate use of data is to draw meaningful insights from which can then be put to use to practice. Data analysis helps in doing this by transforming raw data into a human or machine-usable format from which information is being drawn.
Also Read: What is Data Analysis and Who Are Data Analysts?
Some ways in which data analysis can be distinguished are as follows:
- Organizing data: Raw data collected from single or multiple sources may be disorganized, or present in different formats. Data analysis helps in providing a form and structure to data and makes it useful so that other tools can be used to arrive at findings and interpret the results.
- Breaking down a problem into segments: Working on data collection from an extensive survey or transaction and consumer behavior data can become very challenging due to the sheer volume of data involved. Data analysis techniques can help segment the data thereby reducing a massive, seemingly insurmountable problem, into smaller parts which can be relatively easily tackled.
- Drawing insights and decision-making: This is the aspect which is most readily associated with data analysis. Tools and techniques from the field applied to pre-organized and segmented data assist in drawing meaningful insights which can either help in concluding a research project or support business in understanding consumer behavior towards their products better.
Further, through data analysis in itself is not a decision-making process, it certainly does help policymakers and businesses make decisions based on insights, information, and conclusions drawn while researching and analyzing data.
- Presenting unbiased analysis: The use of data analysis techniques helps ensure that unwarranted biases – human or statistical – are reduced at least or eliminated at best. It helps ensure that top quality insights can be extracted from the data set which can help in taking effective policy actions or decisions.
Some people misconstrue data analysis to be just the presentation of numbers in a report based on which researchers support their thesis or managers take decisions. This is far from being true. More than merely data collection, data analysis helps in cleaning raw data, dissecting it, and analyzing it. It can also assist in presenting the insights drawn or information received from this exercise in a format which is compact and easy to understand.
In companies, there are data analysts and data scientists who are responsible for conducting data analysis. They can play a crucial role in harvesting information and insights from the data collection and study cause and effect relationships by understanding the meaning behind figures in light of business objectives. They are trained to process technical information and convert it into an easily understandable format for management.
Some data analysis methods that they use include:
- Data mining: This studies patterns in large data sets – also known as big data – by applying statistical, machine learning, and artificial intelligence methods.
- Text analytics: It processes unstructured information in text format and derives meaningful information from it. It also converts this information into the digital format for use by machine learning algorithms.
- Business intelligence: This method draws insights from data and converts it into actionable information which is used by management for strategic business decisions.
- Data visualization: This method uses data analysis tools to present trends and insights visually, thus making data more palatable.
Companies like Amazon and Google have made pioneering efforts in using data analysis by applying machine learning and artificial intelligence to create end-user experience better. Given that we are living in the information technology age, the use of data analysis is expected to increase manifold in the future and enhance its scope.
Also Read:
Top 5 Data Science Trends in 2018!
Data Science in today’s world is a combination of various functions – AI, Deep Learning (real and hyped progress), Quantum Computing, Big Data, IoT, and many more such applications which are used together as a network. 2017 was dominated by advances in the AI space which had taken over from Big Data. Data has become popular due to the open-source regime which is slowly chipping away at the market and technology shares of established names like Oracle and Microsoft. With the ever-increasing popularity of newer and scalable programs, let us see the top trends to expect in 2018.
Also Read: How to Become A Data Scientist?
Regulation
The awaited impact-event will be GDPR (European General Data Protection Regulation) which will become enforceable on May 25, 2018. This regulation will affect data science practice in three areas – limits to be applied on data processing and consumer profiling, “automated decision making” and the right to an explanation for that, and feeding in biases and discrimination in automated decisions.
The measures under this act were approved by the European Parliament on April 27, 2016, and will go into effect on May 25, 2018. The law will focus on the new rules on the collection and management of personally identifiable information (PII) of EU citizens. Implementing these rules will bring broad changes in the big data modeling and in creating predictive models.
Artificial Intelligence
According to Garter’s list of Top 10 tech trends in Big Data, it is laying the foundation of AI across organizations. It will remain a major challenge and work plan to follow through till at least 2020 as significant investment in skills, processes and tools will be required to exploit these techniques.
Intelligent Apps
These will be created and used with an aim to enhance human activity and effort and mostly not replace it. Augmented analytics is a strategic growth area in which machine learning will be widely used to automate data preparation, insight discovery, and sharing for a large range of business users, operational workers, and citizen data scientists.
Virtual Representations of Real-World Objects or Systems
Digital representations of the real-life objects will be a common reality and their inter-linkages will help in checking the cause and effect changes for improving the operations and value. It is predicted that over time digital twins of every physical reality will be available and infused with AI capabilities to enable simulation, operation, and analysis. This will particularly help in fields of city planning, digital marketing, healthcare, and industrial planning.
Cloud to the Edge
Edge computing works to maintain the closeness of processing, content collection and delivery close to the source of information. This helps in reducing issues to latency, bandwidth, connectivity. Garter predicts that pairing this strategy with cloud computing will give the best of both the worlds to create a service-oriented model and a centralized model and coordination structure.
While many trends will take a long while to cultivate from its conceptual stage to a working philosophy, these trends will lead the way for future innovations.
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Salary Trends in Big Data Industry
Salary Trends in Big Data Industry
Big Data Industry has become the modern equivalent of the hot cross buns of the mid ages. This industry acts drives people like a moth to a flame, especially those in the field of information technology. If you happen to be one such enamoured individual then as a part of being a data aspirant, you are sure to have a number of questions regarding the field. Your questions will range from any of the following:
- What salary should one expect in this field?
- What are the skills that a person needs to acquire in order to get an entry in this industry?
- What are the many locations where the most amount of opportunities make up a huge chunk?
So if you do happen to have these many questions and if you are shaking your head vigorously in appreciation, then this very article is for you. Read on to dispel all of these questions and find the most proper answers to them.
Recently a very esteemed and astute industry report was released, which spoke about all the latest trends and the insights in the field of big data science, including which tools are very much in demand, to what kind of salary is drawn by some of the most famous of professions and positions.
So far as the report goes, machine learning happens to one of the skills that takes away the cake. It is undoubtedly the best paying skill on the market. At the same time if an individual also happens to have perfect big data analytical skills, then the combination is a lethal one in terms of securing a high paying job. As this trends seems to be one which will have a sizable impact on the future, many are recommended to take note of it.
Earlier days were replete with the rule of licensed data analytical tools like SAS ruling the roost, but today it is the open source analytical tools like Hadoop, R Programming and so on that are gradually coming to power. Tools like Python and R Programming have effectively replaced SAS as the key player and ensure more pay to those with expertise in these tools. Investing more time in these and getting trained is a great choice to follow.
Another trend that is rapidly being taken over by various big guns of the industry like Google is hiring of candidates who have dual expertise in the data analytical tools like SAS and Python, R and Python and so on. Mumbai continues to be the city where data analysts are paid the most, which is followed by Bengaluru and Delhi. Increment and promotions are usually dependent on your educational background or the fact that you’ve done some course or the other. This is why many individuals today have begun to opt for professional training courses in various data analytical tools which are offered by institutes like Imarticus Learning. These courses help them become entirely industry endorsed and jumpstart their careers.