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How Big Data Is Changing Disruptive Innovation?

Posted on by Imarticus Learning

 

How big data is changing disruptive innovation?

It is for sure that big data has grabbed the attention of many as the businesses have understood its prominence in this technology-driven world. The meaning of big data goes by its name it refers to a large sum of data to be handled efficiently for a productive business. Online giants who rule the world of technology like Amazon, Facebook, Microsoft, and Google together store about 1.2 Million terabytes of data.

Which is really a staggering amount of data and now we know how influential are they to the society. A new update from DOMO states that approximately 2.5 quintillion bytes of data is being generated every day and the number is going to increase exponentially. So, this has ideally remarked an era where talented data scientists are on a pinnacle and young aspirants choose data analytics training to land on their dream career.

Understanding disruptive innovation

Well, you must read somewhere that “90% of the world’s data is being created in the last couple of years” this is credited for the growth of online. Disruptive innovation can be termed as a new concept or model which alters the function of the monotonous market and influential in creating a new flow in the market. This disruptive innovation creates a disorder in the market place with its bang.

Impactful big data on the limelight

We often notice new innovations in technology and the way it affects business. Off-late Big data technologies like Hadoop and NoSQL has created quite a stir in the minds of businesses about convincing the customers.  Wings of big data like big data analytics course are vital for data science aspirants to identify hidden patterns to understand customer preferences. Big data has jeopardized the conventional flow of the market by inducing advanced computing and eliminating the traditional way of computing for better business.

Let us look into four ways by which big data is changing disruptive innovation:

Big data proved trust-worthy

You may notice that when new technology is introduced in the market, the market takes a while to completely adopt it. But this was not the case with big data due to its flexibility and impressive tools used to leverage profitability in business. Companies invest in employees who learn these tools to keep them par with the trending market scenario.

Ease of access and flexibility

The smooth transition in the software we use in mobile and computer systems induced by big data is quite enjoyable and user-friendly. Users have become more dependant on big data for it has altered the prospects of users on new technologies. Thanks to Hadoop and NoSQL technologies of big data which has created a revolutionary impact on businesses.

Spending for a positive impact

The need for big data and data analytics is different for different companies. Hence, the money spent on big data also varies. But, the companies are spending a huge sum on big data confidently as it proves to be worthy enough. Businesses pay for big data but proper use of tools and techniques in big data may eventually lead to saving a lot of money. It is a kind of predictive science which monitors previous trends and forecasts future trends.

Action and accomplishments

Big data has been successful in creating a satisfied customer base for business by identifying and understanding the needs of the customer beforehand and diverting the business to concentrate on the right track. Target marketing strategy in big data has aided businesses in achieving long-term growth and stability. When new technology enters the market, it is obvious from the customer end to expect certain changes in its attributes, whereas big data leaves the customers surprised with its functionality which other disruptive inventions failed to do so.

To sum up

Convenience and usefulness of big data have made people realize the way a disruptive innovation should work like. When innovations meet the expectation of the customers it is accredited as a technology that helps a business in gaining a competitive edge. Unlike other disruptive innovation, big data is assisting businesses in identifying market trends and disruptions to grab the opportunities, upon failing to take the first step the competitors will surely do so.

For more details, you can also visit – Imarticus Learning and can drop your query by filling up a simple form from the site or can contact us through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Bangalore, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

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

Posted on by Imarticus Learning

 

Should you start with big data training or learn data analytics? Which one should I start first?

We live in a highly interconnected and dependent world of technology wherein the amount of technology we use is like a drop in the ocean. At the pace we are traveling in this digital world approximately 2.5 quintillion bytes of data is generated on a daily basis. Yes, it is indeed a staggering amount of data that is being produced.

So, the application of analytics in Big Data has various merits for businesses. Hence, businesses look forward to using this to gain a competitive edge over their competitors in the foreseen future. Though businesses understand the prominence of big data they are unaware of using big data to achieve the desired success.

So, ideally, there is a huge scope for talented who are capable of stimulating the business in the route of success using big data. For data science aspirants it is a wise choice to start with big data training than Data Analytics Course. Read on to know more about it!!

Difference between big data and data analytics

The primary difference between the two is that big data is centered around figuring out meaningful insights within a large pile-up of either structured or unstructured data whereas data analytics is more focused and looks out through relevant data to solve business problems.  Big data training consists of complex skills which will be a great addition on top of your knowledge in statistics, database topics, and programming languages. You can also see that most companies are dependant on Hadoop training which essentially helps you to assimilate the huge data using programming languages like Java, C, Python, Swift, etc.

On the other end, Data Analytics Training on operational insights of the business by making predictive models using programming languages and uses manipulative techniques for understanding the trends. Understanding historical data and extracts interferences from it to solve complex business issues.

Tools and skill sets that differentiate the two courses

Typically having good insights about databases, programming languages, frameworks like Apache and Hadoop and coding would help you positively for big data training. Basic knowledge of statistics and mathematics is essential along with creativity to filter a large database. Knowledge about statistics and mathematics along with data wrangling is required to become an expert in data analytics.  Big data utilizes complex technological tools whereas data analytics uses statistical and straightforward tools.

Various tools like Hadoop, Tableau, NoSQL, R and many more are used to draw interference from big data to get desirable graphics, statistical data, and visualization. Learning R programming language is essential to learn Data Analytics due to its widespread use of tools to deal with statistical and analytical data. So, R developers have an edge over others in learning data analytics. Whereas Big data efficiently uses MapReduce, a programming model for processing huge amount of data.  When MapReduce is coupled with Hadoop Distributed File System (HDFS) for its efficient use in Big Data.

What should you do to master big data?

In the bustling world of digital technology, we have access to any information presented by experts in the field of data. Enrolling in either big data training or data analytics courses will definitely be useful to fill the gap between the demand and supply in big data. Having a diversified skill set will give you an edge over your competitors. Big data training and data analytics classes are available online in reputed institutes who provide hands-on training to understand and interpret the concepts in real-time business situations. Look out for training institutes who provide comprehensive insights and training in big data for gaining proficiency in the subject right now.

Conclusion

With an acute shortage of skilled in the field of big data, its demand is set to increase and is deemed to be a long-term growth-oriented career option. As you can understand one course is used to manage large sets of a database, on the other hand, another uses such a database to gain meaningful insights. Learning Big data training may be a smart option for landing in your dream job, it is your call to take up either of the courses first. Take a step forward right now to taste success in the near future!!!

For more details in brief and further career counseling, you can also search for – Imarticus Learning and can drop your query by filling up a form from the website or can contact us through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Banglore, Hyderabad, Delhi,  Gurgaon, and Ahmedabad.

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

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“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 are Online Retailers Using Big Data Analytics?

Posted on by Imarticus Learning

Data is being generated at every moment of the day and has grown from retailers using their own data to databases available across industrial verticals. It is so huge that cloud storage is now the buzz word. Data analytics with the Big tag deals with data primarily and the predictions or forecasts from analyzing databases that help with informed decision making in all processes related to business. This could run into volumes of several petabytes of data.
But, why would one need a Big Data Analytics Course? Because smaller databases that are less than a terabyte size-wise can be tackled with traditional tools. However, modern data tends to be unstructured and comes in the form of videos, audio clips, blog posts, reviews, and more which are challenging to clean, organize and include huge volumes of data.
The tools and techniques involved in the capture, storage, and cleaning of data need necessarily to be updated. One also would need faster software that can compare databases across platforms, operating systems, programming languages and such complexities of technology.
The speed and agility of analytics offer big advantages and savings in making informed business decisions. That’s why investing in data analytics and Data Analytics Training is such a popular choice across industrial verticals and sectors.
Let us look at the data analytics improvements of some real-life examples.

Offering marketing insights:

Foresight from analytics has the potential to change marketing strategy, operations and more in all firms. Whether it be effective marketing strategy or promotional campaigns, decision making, purchasing, cost-saving measures, targeting the customers, promoting products or improving efficiency through the predictions, insights, forecasts, etc help make those decisions. Just look at the campaign of Netflix covering over 100 million customers for inspiration.

Boosting retention and Customer-Acquisition:

Coca Cola used their data foresight to draw up their retention and loyalty reward programs and to improve their services, products, and customer stories. Besides boosting sales such improvements trigger loyalty too.

Regulatory compliance and Risk Management insights:

Singapore based UOB did their risk assessment and management for the financial sector and budgeting. Foresight and predictions can also be effectively used as a critical investment in regulatory compliance.

Product innovations:

Take the example of Amazon’s diversification into groceries, food, and fresh-foods segment. Their analytics program was based on the acceptance of customers trends and successfully helped innovate product lines, design models of innovation in saleable products, etc.

Management of logistics and supply-chains:

This essential field can be transformed very effectively as Pepsico did with improved processes, scheduling deliveries, warehouse management, reconciling logistics and shipment needs and more.
Budget and spending predictions:
The loyalty of customers is reflected in spending patterns and data is collected from use of credit cards, effects of promotional programs and customer retention data, web users log-in data, IP addresses, etc to gauge predictions for spending and effective budgeting. Did you know that Amazon analyses accounts that run into astounding figures like 150 Mil customers and their analytics programs increased sales by 29 percent and new customers by 40 percent? That’s huge profits from data analytics!

Bettering customer service:

Improvement in customer experience yields big dividends as in the case of Costco where specific customers who were at risk with listeria contamination in fruits and were warned instead of creating a scare with emails to all customers.

Demand forecasting:

Just look at the Pantene and Walgreens hair-care products sales figures. They promoted the products based on a demand prediction of weather and anticipated higher humidity affecting sales of anti-frizz hair products. Pantene recorded a 10 % increase and Walgreens a 4% sales increase. Smart use of data analytical predictions by retailers!

Research on journeys of customers:

This graph is never a straight line and when in retail marketing analytics with many thousands of customers, one can help understand data like where an individual customer will seek product info, how and where to reach such customers, why the customer loyalty changed, etc. Looking for the needle in the haystack is now easy with data analytics.

Concluding note:

All enterprises, especially in the retail sector, need big data analytics to have reduced operational expenses, a competitive edge, enhanced customer loyalty, better productivity, and retention. The demand for data analysts keeps growing alongside the growth of data and is an ideal choice of careers with scope, payouts, and growth. If you wish for a Data Analytics career, then do a big data analytics course at the reputed Imarticus Learning. Their data analytics training with assured placement, certification, soft skill modules,industry-suited curriculum, and real-time project work offers the best career choices. Enroll today!

Why do Corporates Need Big Data Analytics Training?

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Why do Corporates Need Big Data Analytics Training?

Data is an invaluable organizational asset in modern times since big-data is being exploited for its value in providing business foresight and predictions based on analytics.

ML, AI, and deep learning algorithms are applied to massive data volumes to provide corporations with the opportunity to use their data to tweak their measurable efficiency, and the decision-making process, and also reach out to a larger number of employees at the same time.

And, data analytics training on big data is no single program. It is a technology combination that helps the corporations extract the best value from data and analytics tasks. 

Corporate advantages:
The important plus factors of data analytics for corporations are explained briefly below.

Database Management: Data can be from different sources and in various formats. Its quality and organizations are of prime importance before going in for big data analytics. 

Since in most large corporations the data travels from department to department, and various subsets may be added or deleted as the case may be, it becomes necessary to have an established repeatable process and a master management program format to maintain the quality of the organizational data. This ensures that the management of data is in synchronization across the organizations.

Mining and modeling of financial data: The technology for this task allows the examination of several petabytes of data produced by the moment. This task will enable you to sift through the data for relevance, and then use the subset for predictions and forecasts which hasten the decision process and in turn impact informed decisions being taken for critical and strategic decisions by the management.

Pricing and modeling using ML: ML trains the machines and AI to help it learn to recognize the patterns involved. This hastens its self-learning process and allows the algorithm to automatically move through more complex data models and still deliver accurate and desired outcomes.

This Big Data Analytics Training capacity is invaluable, especially where unknown tasks and risks are involved or where models need to be continuously auto-generated.

Storage and engineering of Big-data: Hadoop is a commonly-used, free and open-source framework which uses clustering of information on hardware to store larger amounts of data. Since data continually increases in volumes, types, and sources, the Hadoop models used for computation handles very big-data volumes and needs no license. It thus allows for using demographics, sensor data, driver data and market information all on the same platform. The best example here is of the 2000 crisis in Ford and how it overtook the competition in Asian and European markets.

Product development and analytics in-memory: Instead of using the hard disk, such a facility allows the access of data from the system memory instead. This allows quick decisions, analytics and predictable outcomes from the organization’s data. One of the most significant advantages of the system memory is that it is iterative, agile, removes latencies in processing and data preparation while providing for quicker and better decisions and analysis that is interactive especially in product development and modeling.

The task of Predictive Analysis: Here, the technology used consists of algorithms based on statistical modeling and ML techniques. Large corporates use their data for gainful business outcomes based on Big Data Analytics to make the best decision in any given scenario.

Marketing, risk assessment, and fraud detection are just some of the areas that benefit from such analysis. Were you aware that Singapore based OCBC used such insights to achieve a new customer increase rate of 40 percent?

HR capabilities and mining texts: The latest improvements are used to analyze data from text messages drawn from the surveys, comments, Twitter, web posts, emails, blogs, books, and such text-using sources. Such analytics is beneficial in strategizing for competitive leadership, the introduction of new products, newer areas for development, and establishing loyal customer relationships both within and outside the organizations.

Parting notes:
Training and cleaning of data are very important to organizations to take quick and effective decisions at the right time, especially when it comes to strategic and critical business decisions. Since data analytics comprises of a series of technological programs executed in systematic models, it is essential to do a data-analytics course before one makes a career in this field. The scope for such jobs is indeed never-ending because of the sheer volumes of data being generated and available for analysis.

Doing your course with the reputed Imarticus Learning ensures you are job-ready, proficient in data analytics and get a chance to hone your presentation skills too through the soft-skills modules. Top this with certification, and you are all set to start a great lucrative career. Do you have any more doubts? Get in touch with Imarticus today.

Can you become a Data analyst by online tutorials?

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In an age where tutorials and lectures are heavily sought after both online and offline, it is easy to see why online tutorials are on-demand, especially to those who are already occupied with jobs with heavy schedules and those professionals who experience time constraints to attend an actual full-time offline course. Although the teaching methods, means, and experience of that of an online tutorial may be quite different, if you are a good self-starter and self-learner, it is quite an engaging and educative activity you can invest your time in regularly.
Let us understand how to learn Data Analytics through online tutorials will guarantee you in becoming a Data Analyst professional. Some of these points are discussed below –

  1. Avail Online Big Data Analytics course for a minimum fee– Regular online classes, engaging, recorded lectures and practical projects help you gain great insight and enhance your skills regarding your subject matter. There are various online options for you to register and enroll for a course in Data Analysis. It sometimes has payment requests and you will need to pay the required fee for accessing these classes. To maintain a certain quality and standard some of these courses are priced with a standard fee structure.
  2. A wide variety of knowledge base in Data Analysis to choose from – You can choose from various types of Data Analysis courses that have the online classes option. From the IBM Data Science Professional Certificate to Applied Data Science with Python to Business Analytics to learning the Data Scientist’s Toolbox, the choices for you to pick from are vast and varies, giving you the opportunity to truly specialize and focus on your favorite subject matter.
  3. Globally recognized online courses – Not only do you have the benefit of investing only a small amount for your Data Analysis certification course, but you will also have global validation for the said course(s) This added advantage makes your knowledge base, skills, tools and techniques learned under the course internationally relevant. This naturally means a great score of career options and job opportunities will now be open to you.
  4. Free courses – Sometimes there are courses offered absolutely free of cost. Data Analysis has several such courses offered free of cost. The option of the syllabus may be limited but you will gain a little above the general knowledge of the certification course and will be able to become relevant with the skills and knowledge you achieve through this online engagement.

From the above factors it is evident that through practical application, patience and practice, you can forge into a  professional Data Analyst career with online support and tutorials. If you expand your knowledge base, there are further professional certifications and degrees to be awarded too. This is available online as well. However, the fee and eligibility criteria may vary accordingly.
So, go on, search for that perfect online course or online tutorial and equip yourself in becoming the best Data Analyst you know. With basic know-how, a minimum investment of money and time, practice and consistent efforts, turn your Data Analyst dream into reality!

How is Big Data Analytics Used For Stock Market Trading?

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How is big data analytics used for stock market trading?

Big Data Analytics is the winning ticket to compete against the giants in the stock market. Data Analytics as a career is highly rewarding monetarily with most industries in the market adopting big data to redefine their strategies. Online stock market trading is certainly one area in the finance domain that uses analytical strategies for competitive advantage. 

Capital market data analysts are important members of a corporate finance team. They rely on a combination of technical skills, analytical skills and transferable skills to compile and communicate data and collaborate with their organizations to implement strategies that build profitability. If you’re interested in a career in financial analysis, there are several subfields to explore, including capital market analysis.

Organizations and corporates are using analytics and data to get insights into the market trends to make decisions that will have a better impact on their business. The organization involved in healthcare, financial services, technology, and marketing are now increasingly using big data for a lot of their key projects.

The financial services industry has adopted big data analytics in a wide manner and it has helped online traders to make great investment decisions that would generate consistent returns. With rapid changes in the stock market, investors have access to a lot of data.

Big data also lets investors use the data with complex mathematical formulas along with algorithmic trading. In the past, decisions were made on the basis of information on market trends and calculated risks. Computers are now used to feed in a large amount of data which plays a significant role in making online trading decisions.

The online trading landscape is making changes and seeing the use of increased use of algorithms and machine learning to compute big data to make decisions and speculation about the stock market.

Big Data influences online trading in 3 primary ways:

  1. Levels the playing field to stabilize online trade

Algorithmic trading is the current trend in the financial world and machine learning helps computers to analyze at a rapid speed. The real-time picture that big data analytics provides gives the potential to improve investment opportunities for individuals and trading firms.

  1. Estimation of outcomes and returns

Access to big data helps to mitigate probable risks in online trading and make precise predictions. Financial analytics helps to tie up principles that affect trends, pricing and price behaviour.

  1. Improves machine learning and delivers accurate predictions

Big data can be used in combination with machine learning and this helps in making a decision based on logic than estimates and guesses.  The data can be reviewed and applications can be developed to update information regularly for making accurate predictions.

In a nutshell, large financial firms to small-time investors can leverage big data to make positive changes to their investment decisions. Information is bought to the fingertips in an accessible format to execute trading decisions.

If you are a trader, you will benefit from a Big Data Analytics course to help you increase your chances of making decisions. It is highly beneficial for those involved in quant trading as it can be used extensively to identify patterns, and trends and predict the outcome of events. Volume, Velocity, and Variety are the pillars of Big Data that aid financial organizations and traders in deriving information for trading decisions.

How Analytics And Data Science is helping OYO To Enhance Customer Experience?

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How Analytics And Data Science is helping OYO To Enhance Customer Experience?

According to the CEO and Founder of OYO Rooms Ritesh Aggarwal, the use of analytics and data science helps identify not only the right demand but also the right action for each customer to enhance their experience. Its pan-India 223 city presence boasts of over 2 million check-ins and a total worth of 260 million dollars currently. OYO has used data science technology and analytics successfully in the hotel booking and servicing of accommodation renting segment tapping the mobile users who use the internet and advancements in technological apps to get the best deals and prices.
The OYO story:
In May 2013 OYO started with one hotel booking and had grown to over 8500 hotels and 75K rooms spread over well-targeted metros, commercial hubs, small cities, pilgrimage towns and foreign leisure destinations like Nepal, Malaysia, etc. Their analytics and data science efforts helped provide unmatched prices for well-stacked and standard hotel services while setting the bar for in-room customer experience and budget-accommodation availability in India. OYO’s inspirational story is the result of its CEO’s entrepreneurial debut, and his success is truly inspirational.
Offering standardized stay experiences OYO is spread across 223 cities in all We have revolutionized the legacy-driven hospitality space in India by standardizing the in-room experience and delivering predictable, affordable and available budget-room accommodation to millions of travelers in India,” says Ritesh Agarwal, founder, and CEO, OYO Rooms.
Ritesh hails from Orissa and travelled from the young age of 17 to many hundreds of B and Bs, hotels, resorts, guest houses, etc. to make a curated list of them and help discover such locations that were obscure till date. The introduction of price affordability, standardization of services and customer behavior predictability were the contributive factors to overhauling the way and use of booking with OYO and its analytics and data science program. The importance of training and experience in predictive analysis, data analytics, handling of big data of several petabytes, creating smart self-learning algorithms, and using the latest techniques of neural networking of the ML with AI cannot be undermined according to Aggarwal.
OYO and technology:
The services provided with OYO bookings are standardized with customers getting ac rooms, flat-screen TV, 24×7 customer support, WiFi, complimentary breakfast, quick availability searches, and app-based booking. Of course, the comfortable customer experience brought loyalty and increased its app reach and revenues by leaps and bounds. The app saw 5 million downloads in the first few weeks and OYO cashed in on data of room searches, availability, fair pricing, standardized services, etc. through its analytics-supported app.
Additionally, cab bookings, room-service requests for beverages, laundry, food, etc. were linked in through smart neural networking to provide a seamless 5 second 3-tap experience. Thus sales, technology, intelligent data analytics, satisfied, loyal customers and owner engagement driven by the analytical ability of the app helped OYO emerge as the 2018 unicorn amid the disrupted industries and stiff competition from CoHo, NestAway, ZiffyHomes, Homigo, WudStay, and SquarePlums.

The analytics and statistics:
According to an HVS report cited by Ritesh Aggarwal, unbranded hotels numbering 2 million are available as against the 112k branded ones. That is a huge, potentially untapped customer market that OYO plans to utilize in its growth to make OYO services a household name and brand to reckon with. Even the funding of OYO was strategically planned to raise 260 million dollars from Sequoia Capital, SoftBank Group, Lightspeed, and GreenOaks Capital. It hopes to raise its capital to over 500 million dollars with SoftBank’s help putting it in the unicorn league.
Parting notes:
Whether it be a bus booking, a train reservation, a connecting flight, the last-mile cab availability, intra and intercity travel, long or short stay vacations, quick food, and laundry services, or undiscovered destinations, OYO has plans to keep its customers numbers growing by catering to their needs reflected in the smart analytics app and media. Their inclusion of shared vacation stays, resort accommodation, and service apartments like Chennai-based Novascotia Boutique Homes to their hotel bookings was strategic inclusion planned for the internet savvy mobile user and a trend reflected in the search use of customers in its analytics-based strategic market expansion plans.
Data science analytics is best learned in classrooms with plenty of hands-on and industry-relevant experience. Certification, able mentorship of certified trainers and an assured placement program gives such training courses the leading edge in launching your career. If the OYO story inspires you, then do a Big Data Analytics Course at the reputed Imarticus Learning. Perhaps you will also take to utilizing the opportunity provided to get entrepreneurial ideas and mentorship assistance to start a successful venture. All the best!

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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!

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!