What Are The Ways Big Data is Being Used To Create The Next Generation of Mobile Apps?

Big data tops the charts when it comes to providing a considerably better user experience by increasing app engagement and optimizing resources correctly. While it not only makes content for users more relevant but also personalized content and when analyzed from a business point of view, it improves conversion rates. To put it in simpler words, the future of big data is the gold mine that app developers need in providing information and creating apps that users want.

Here is a breakdown of the various ways in which big data is being used to create the next generation of mobile apps:

Seamless and easy to use UX
Big data is incredible in providing insights that help tract every movement of a user by crunching numbers to improve overall user experience. Additionally, it also helps in signaling developers when apps do not meet either the design standards or the UX. Studies suggest that most app users stick to or delete an app based on its user-friendly quotient, which is the ease of use. This kind of information helps big data constantly make improvements for user interface and reduce friction.

Machine learning and artificial intelligence

With the help of machine learning and usage of artificial intelligence, big data can recognize failure patterns if any and suggest improvements.  Also, this helps understand any glitches that might be acting as slowdowns, including loading time for a website or a page.

Predictive analytics and customization
Big data helps customize the user experience and deliver content based on previous usage patterns. This is where predictive analytics come into play by suggesting what you should buy or what you should watch. This gets increasingly better as you consistently use a particular service.

Widely used by companies like Netflix and Amazon, predictive analytics shows up an image or shows pricing options based on user data buying patterns and more. Basics of predictive analytics are taught during a Data Analytics Course.

Increase app engagement

Users often get more engaged with a particular app and keep returning to it frequently. A term referred to as- app stickiness, this actively engages customers more than its competitors and factors like duration session, the flow of content on the screen and churn tracking help in contributing to stickiness.

Real-time analytics

Real-time analytics help an app developer to analyze data related to that app and make dynamic changes based on the present situation. The mobile app market in itself is a pretty dynamic one, where things significantly change every minute. Organizations are using real-time analytics o predict patterns that include flying for airlines when visibility is good, avoiding certain roads to get rid of traffic, avoiding extreme weather conditions, sharing driver and customer live locations, estimates fares at a given point in the day and more.

Evolve marketing strategies

Big data can help make better marketing strategies, by capturing user data that helps app developers understand the kind of people their users are. Existing strategies are reworked on to reach out to new users and rearrange older users. Study of user demographics, buying patterns social behavior of apps, posts liked, websites visited, all of which can be used to build individual user personas which are then used to strategize marketing strategies.

Considerable cost reduction

Lastly, big data helps understand and predict app development costs, since building a standard app might often be time-consuming and quite expensive. This not only includes the app development process costs but also calculates the number of developers, designers, testers and more will be needed to have an app up and running. Additionally, the longer time it takes to build the app, the higher the cost graph goes.

What Are The Tips To Prepare For a Hadoop Interview?

The popularity of big data has been growing at an immense rate opening the doorway to a spectrum of jobs that require skilled professionals. Noteworthy among these is the job of a Hadoop developer; challenging, technical and well paid, Hadoop is known to be one of the best segmentation of big data and analysis and a developing platform for candidates interested in a career in data science.
Learn Hadoop to pursue a career as a Hadoop analyst, Hadoop developer, or a Hadoop Architect, Hadoop tester among other job roles on the Hadoop platform. If you are looking for a career in this domain, it is highly essential to understand that a Hadoop developer not just created codes in programming but is also expected to have an expertise of multitasking while as his job, which includes programming in Java, writing scripts, reviewing log files, scheduling jobs across clusters on Hadoop amongst others.
Basic skill set for a Hadoop interview
Hadoop works with a number of other software like Ambari, HBase, Hive, Pig and more, therefore, knowledge of technologies is essential. While it is important to also have an idea about other visualization and ETL tools, SQL, gateway and edge nodes, basic cloud computing, some of the must-have skills an interviewee needs to possess during Hadoop training include JAVA, Hadoop Framework, Pig, HDFS, MapReduce, and Floop.
Tips to prepare for a Hadoop interview
Cracking a successful Hadoop interview does not essentially mean having specified skillsets but also ensuring that all of the interviewee’s questions are addressed. While Hadoop in big data is a relatively new concept, here are a couple of tips to help you prepare better for an upcoming Hadoop interview.
Knowledge of Programming Languages
Java experience is as important as it can since Hadoop is a software-based on Java. If your career path monitors progress from C++ to Java, nothing like it. Knowledge of other programming languages like OOAD, JS, Node.js, and HDFS only add to your skillset and make your resume stand out from the rest of the candidates.
Big Data experience
If you have experience working with big data, a Hadoop interview would be fairly easy to crack, since Hadoop is mostly built for the working of big data.
Technical Expertise
To crack a Hadoop interview, you not just need hard skills for Hadoop but also various other technologies that include Flume, Sqoop, Hive, Pig and more. These technologies often seem smaller, however, they make data processing easier on Hadoop.
Interview domains that are essential to prepare for
Along with a good grasp of relevant skill sets, listed below a couple of interview domains every interviewee needs to prepare for-
Practical experience
Theoretical knowledge is important, however, most interviewees are tested on practical knowledge. Expertise in the practical field subjects candidates to various degrees of exposure otherwise impossible by merely learning theories.
Communication Skills
Hadoop experts have to communicate with people in various other job roles, that often include engineers, analysts or even architects. In cases like these, good communication goes a long way.
Knowledge of domain
The interviewee is expected to know the A-Z of Hadoop along with its basic functionalities. You may be expected to back your interview answers with sufficient theoretical or analytical examples.
Conclusion
Big data is growing at an immense rate and more professionals are getting enthusiastic to work in the field. An extensive Hadoop training can go a long way in helping a big data enthusiast to master the best skills in the market and make it big as a professional.
For more such information, feel free to visit – Imarticus Learning

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!