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Tag: Big Data Analytics Training

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.

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.

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.