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Tag: Big Data Analytics Training

Should You Start With Big Data Training Or Learn Data Analytics?

Posted on by Imarticus Learning

While the difference between Big Data and Data Analytics isn’t huge, it’s an important one. Career streams in Data Science can diverge into two separate branches based on which one of the above you choose. 

Both Big Data and Data Analytics focus on the same thing – processing large chunks of data for valuable insights. But the methodologies and tools used for the same are different. Therefore, you can choose to specialize in one career stream and continue progressing in it, or you can learn both. 

In order to make a clear distinction, let’s define both the streams separately. 

What is Big Data?

Big Data refers to the management and operations performed on extremely large data sets (one data set is often greater than 100GB) in order to extract patterns, trends, and insights that can power business decisions. Therefore, you have to cultivate expertise working with a large amount of data, and meet specific challenges that it presents. 

 

  • What all you learn in Big Data Analytics Training?

 

  • Data optimization techniques. 
  • Finding relationships and patterns. 
  • Big Data tools such as Hadoop, MapReduce, etc.
  • Compiling, sorting, and processing data using Python, R, etc.

What is Data Analytics?

Data analytics deals with obtaining relevant and very specific information out of smaller data sets. Where a Big Data analyst will sort through millions of rows of data, a Data Analyst will work on finding the statistical parameters in a given range. It involves reporting of elementary but well-defined parameters than can be analyzed for business value. 

  • What is taught when you learn Data Analytics? 
  • Applying statistical principles to data sets. 
  • Compiling and disseminating information from data sets. 
  • Generating goal-oriented reports for decision-makers. 
  • Working with analytical techniques for smaller data sets. 

Which one to learn first?

  • Direct Path 

At Imarticus, we have made both the options available to the students. They can dive straight into Big Data Analytics Training which will prepare them for Big Data from grassroots levels.

Learning Big Data directly ensures that the students are absorbing the concepts they’ll use in professional places directly. They’ll be trained on various tools used in Big Data so that they can come to speed with the industry scenario. 

Same is the case with Data Analytics. Students can learn Data Analytics directly and make it as their career objective. In case they don’t want to get into Big Data, this is an excellent Data Science alternative for them. 

  • Progressive Path

The second option available to students is to specialize in both Big Data and Data Analytics but in a progressive way. They’ll study Data Analytics first and then shift their focus to Big Data. 

Although there is a significant difference between the two career streams, the underlying concepts remain the same. Therefore, someone with the knowledge of Data Analytics will not find it difficult to make the switch. Rather, they’ll be able to advance their career at will. 

Conclusion

As Data Science flourishes as a career, Big Data and Data Analytics continue to be the two best career streams in the market. Our courses cater to both the streams exclusively, as well as, in an integrated way for students to plan their career logically.  

How Big Data is Implemented in Business?

Posted on by Imarticus Learning

Big data is everywhere, and behind every organized solution, you face on the daily. The term refers to massive sets of data that inundate businesses during day-to-day operations– but it’s not the data dump itself that matters to businesses, but the goldmine of insights it reveals once it’s sifted through, analyzed and put into plain and simple words.

The amount of data an average business sees in a day is torrential. Big data scientists find themselves having to deal with the ‘three V’s’ as they’re called:

  • Volume: tonnes of data from a dozen different sources including social media and daily transactions
  • Variety: structured and unstructured data; numeric or stock; video or audio
  • Velocity: Breakneck speeds at which data flows in from all channels into the dump

Big data is highly complex and interrelated, which means sifting through and making sense of it can be quite the herculean task. However, the insights gathered through the process of going through the dump can enable reductions in costs, effort and time. It can also open up new revenue streams, enable the development of new products and bolster analytical and strategic business decision-making.

How is big data implemented in business?

The traditional method of storing data is by using relational database software, built for Structured Query Language (SQL). However, the future of big data began looking too complex for businesses to be able to control, which led to the introduction of NoSQL.

NoSQL is customizable and scalable, making them ideal solutions for businesses both big and small. It’s made specifically for big data, and stores data in the following ways:

  • Document storage
  • Graph storage
  • Key-value storage
  • Column family storage

NoSQL provides real-time, super-quick access to data, without the need for schemas and columns. This allows the running of real-time programs towards furthering business processes. Without the schema middleman, data scientists can directly interact with tonnes of data, which in turn saves any business a lot of effort, time and money.

Why is big data important in business?

Industry professionals and students alike are looking to learn big data analytics and science because of the plethora of job options it opens up in the world of business.

Access to information

Bug data opens up new avenues for businesses to explore, be it in terms of generating revenue, introducing new products or strengthening marketing. It enables real-time data monitoring and allows for A/B testing where necessary without too much of an impact on ‘business as usual’ if the strategy doesn’t work out.

Faster decision-making

Hadoop and other in-memory analytics software allow businesses to conduct analyses on information immediately, further enabling them to come to crucial decisions faster and based on data instead of speculation. Big data can also be leveraged to lookup more updated and dynamic data, allowing decision-making to be accurate as well.

Conclusion
As a good data analytics course will show you, big data is in use across several burgeoning industries, each with their own means and end goals. Be it manufacturing, pharmaceuticals, retail or even governments, there is no place big data can’t be implemented– which means there is no place big data specialists can’t go.

Data Analytics Changing the Structure of Media and Entertainment Industry

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Data Analytics Changing the Structure of the Media and Entertainment Industry

Big Data Analytics Course is a highly searched course on Search Engines. Also termed as Data analytics, it is among the indomitable tools that allow businesses to compete in the market. Around 73% of the businesses are involved with Data Analytics in some ways. There is hardly any sector that remains unaffected by Big Data.

The media and entertainment industry are one of the primary adopters of data analytics. The industry generates a huge amount of data, which is basically in digital form. The data also comes with the capability of changing the research space regarding the consumers.

Media and entertainment companies are increasingly transforming and executing Big Data analytics and machine learning in various areas.

Here are some of the primary areas. 

  • Improvised Ad Targeting;

According to the Big Data Analytics Courses, advertising is an important aspect. The concept comes with features like advanced segments, detailed view of customers, hyper-targeted ads, and much more. Working on advanced analytics includes improvised ad targeting to help the correct viewers visualize the ads. Along with the standard advertisements, using video marketing campaigns, social media platforms are also helpful in improving the ad target to obtain data in bulk.

  • Optimization of Media Scheduling;

Data analytics consists of collecting data from various sources to derive efficient predictions regarding the actions of the users. The external sources of data collection are much essential. The detailed predictions would also be more accurate for the complete optimization of the audience for obtaining more views. The companies can also look for personalized advertisers for using the demographic data obtained before.

  • Getting new sources of revenue 

This is among the prime chapters of the Big Data Analytics courses. With the help of data analytics, it becomes easier to get new sources of revenue in terms of media and entertainment. In today’s competitive market, identifying the innovative resources of revenues, apart from the traditional advertising campaigns and partnerships, is considered to be one of the valuable assets for the company. The companies can also go with the digital conversion of the micro-segmented customers for advertising the exchanges and networks.

  • Social Media Analysis;

In the digital market, nearly all companies use social media on a regular basis for proper analysis of the data collected. Be it Facebook, Instagram, Twitter, or any other social media platform, it generates data in bulk, which is helpful in real-time analysis. This is also a cost-effective way of data processing with a large amount of data. For obtaining actual feedback, the usage of multiple sensors for the theaters or smartphones is also an effective way of social media analysis.

Some other applications used for detailed data analytics of the media and entertainment industry include data visualization, inference engines, cross-sell, and many more. Through all these techniques, the companies can easily analyze the services and the data obtained from them, taking all the requirements into consideration.

Big Data is a boon for the media and entertainment industry. Media comes with improved access to the data of the consumers compared to other sectors. By analyzing the data from the content consumed, the users would have a clear insight into the effective formats, consumption patterns and viewing provided. Using the analytical data is also helpful for the media companies in working over various issues regarding the channels and the formats that would attract consumers.

So, are you looking for effective Big Data Analysis Courses? Get in touch with Imarticus Learning for all your needs.

How Big Data Is Changing The Way Marketing Teams Strategies?

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Big data in today’s world
Big data is transforming the way how the world thinks. Corporations have an appetite for data and they churn out almost everything from it be it vital or useless information, segregate the analysis on different parameters and draw out multiple conclusions. Today, we live in a data-driven world where everything from schools to offices, amusement parks to movie theatres runs, etc. runs on data.  Big data has become a very prominent turning point in the history of the world economy, therefore, knitting the world together faster and better.
Importance of marketing
Any company can produce a product or plan out to provide a specific service. The challenge is to take that product or service to millions of people who will then buy those products or avail those services, thus helping the companies to fulfill their ultimate objectives. In such a situation, Marketing comes into play. Marketing is a set of activities which are brought together to increase the mass reach of any company and its offerings. With everything shifting to an electronically operated platform, there is a strong gap that is constantly being filled with online marketing. Businesses are promoted online using multiple online channels such as search, videos, emails, ad campaigns, etc.
Big data and marketing
With the movement of the marketing function to a digital platform, its dependency on big data has become inevitable. Marketing teams of various companies analyze the trends prevalent in marketing using consumer data and come out with various new marketing campaigns to fill these gaps thus helping the businesses to meet and beat their targets. Companies are increasingly spending on mobile advertisements thus catering to a huge audience in a short period. These ads are individual-specific as Big Data Analytics Courses use the residing cookies in your system and display only those products and services which garner the attention of that particular individual.
Marketing and big data: a perfect blend
The advent of big data capturing the market, it has affected the marketing function drastically. It has made Marketing an interactive as well as a very insightful process. Marketers use tools like Google Analytics to know how their websites are performing and how many eyeballs their particular products are turning. Then accordingly they work on the marketing strategies of those range of products and services which are not performing well and also on those avenues which are outperforming to further increase revenues from them.
People spend long hours online thus making online marketing the only resort to reach the audience of this era. People are increasingly responding to online marketing campaigns thus bringing in more and more personal information into the picture. Big data helps in transforming these inputs into final sales and thus converting the desires of people into the business. The data collected in the online platforms will be the deciding factor for your marketing campaign’s success. Businesses will have no clue what’s going wrong in the absence of data.
Digital marketing and big data together have helped in improving the users’ product viewing experience. Marketing teams are constantly looking for new opportunities. Big data provides to be an effective tool in doing so. Also, it gives insights on when a company should pull the plug if something is working against its success. Using big data, every action can be tracked.
By reviewing data analytics, companies can find out how users perceive their business and its products. Using tracking codes, a lot of data can be collected and then segmented into various sections. Data can give minute details such as which ads are making the most revenues, which ads need improvements and which ads are working negatively. Also, companies need a record of conversions i.e. how many ad views are resulting in final purchases.
Conclusion
Big data is playing a major role in formulating marketing strategies. Data provides valuable insights that are further analyzed and developed into a strategy map on how the marketing function has to be taken up. Establishing concrete goals and measuring the fulfilment of such goals has become much easier with the use of big data.
For more details, you can also search for – Imarticus Learning and can drop your query by contacting through the Live Chat Support system or can even visit one of our training centers based in – Mumbai, Thane, Pune, Chennai, Bangalore, Hyderabad, Delhi and Gurgaon.

How Big Data Fits In With The E-Commerce Customer Engagement?

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Briefing the Big Data

If you are reading this wearing the glasses you ordered online, chances are that big data has some role to play in your purchase. If you are unfamiliar with the concept of big data reading the following piece of content here is going to add a whole lot to your knowledge base.

Big data can be understood as a big pile of the database that is amassed over time from various sources called data points, the big data helps in the identification of patterns, trends, and aid in providing useful insights for businesses and other parties in possession of the data. It is generally valued by big corporations to target their customers with ease.

The Virtual Customer

Big data is the norm today no matter what industry are you in, Big Data Training is the ultimate solution in the age of digital data and global consumers. Sales is a smooth sail in the digital ocean, courtesy of the big data!

The digital world has a new way of marketing things, different from traditional means of marketing the online and digital marketing expenditure has different components to it in terms of cost for content and creatives to lure in the targeted customer.

So how do you quantify and asses the performance of your marketing expenditure in the digital world? Well to address this query we have to dive deep in the concept of customer engagement in the dot com world. So customer engagement here unlike the traditional methods of marketing is counted through likes and comments and online traffics on the website.

Among the countless boons of technology, the one counted among the giants is enhanced globalization and making the concept of the world as a global village come to life. This has helped a lot of organizations to increase its customer base globally.

Talking about the businesses whose sole existence is credited to the merits of technology, e-commerce has a lot to be thankful for. Anyone who can connect to the World Wide Web could be a prospective customer.

To determine if you can target the one visiting the world wide web to come to visit your store needs a lot of insight about the visitor’s taste and preference his past track record of purchasing a product and the general trend of things, this is where the big data fits into the picture.

Big data boosting Ecommerce

What has been observed today is that customers are missing the human touch which can be understood in a sense as a personal attention deficit that the traditional brick and motor stores provide to a great extent. In the cutthroat landscape of eCommerce, you can’t just go with one size fits all approach, you have to style your market in a customized fashion making it more personalized for people visiting your E-stores.

Today the customer’s willingness to pay is not just limited to providing quality products, in the contemporary the game has changed altogether, people see everything as an experience, the better you polish that aspect of the business the more probability there is to gain a fair share in the market and retrain the customers.

Big data has amassed the data about all the variables that could possibly affect a buying decision. From personalized gifts to customized loyalty programs it delivers upon all the aspects of personalization that will generate new customers and will help retain the existing ones into the customer list.

Research has also shown that those who are using big data tools for their e-commerce business are likely to be more productive and efficient in their functioning. Big data not only delivers for the sellers on e-commerce but it’s also a magnificent time-saving tool for the customers as it helps them in a lot of aspects, from finding the right product to choosing the best fit.

Selling online is a different story, the big data pumps your marketing by only targeting those who matter based on the past records of purchase and preferences, and this naturally increases the conversion rates and the return on the marketing expenditure.

Conclusion

Big data is a game-changer for the e-commerce business segment given the presence and deep penetration of the digital world. Personalization of products and other customized services is enhanced to a huge extent with the application of big data.

What Are The Ways Big Data Is Changing The Healthcare Industry?

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Introduction

Big data is the new elephant in the room. One can do nothing but notice how fast its applications are increasing and talk about it. Big data has made use of such information which was collected through various systems but was never used. It is evolving with every passing day thus making itself a lucrative investment for companies who want to survive and flourish in this era of globalization and innovation. Big data analyses huge chunks of data a matter of seconds, thus drawing useful insights and also saving time, money and human effort.

The Healthcare industry

The health care industry includes everything from drugs to hospitals, diets to well being and a lot more.  The commercialization of the healthcare industry is growing at an alarming rate. It is one of the fastest-growing sectors involving almost the whole population of the world and loads of money thus forming almost 12% of the economy of any developed or developing nations. This segment has huge potential which was untapped until now.

With big data and analytics taking over the world, the healthcare industry has evolved tremendously. From medical insurance companies to drug manufacturing giants, all of them are minting money by using their data to the fullest, extracting out details one could have ever imagined.

The Healthcare industry and Big Data

The application of big data in the health care world has proved to be again for both – the parties providing services and the parties receiving the services. The big data uses the health data of millions of people to create a digitally empowered market. The big data has served its purposes by controlling harmful epidemic diseases and also curing millions of people. The major application of big data is in optimizing cost structures.

Various hospitals analyze the patients’ data available with them, finding out the intersecting points, working on them and saving millions. Various drug giants analyze their data with the help of big data thus improving their supply chain operations efficiently and increasing the reach of the medicines produced by them.

The health insurance market is a crowded space. The doctors make use of data to understand a particular patient, his medical condition and possible disease thus helping in curating the best insurance plan for that particular individual. This data also helps doctors in new findings and figuring out new innovative ways to cure diseases. Also, big data has not only made the analysis of data easy but also the collection of data a pretty convenient.

Data analytics also provide individuals like us to keep a tap on our general well-being and health. Various applications like Google fit keep calorie counts and heart rate information in data bits helping an individual to monitor his activities and also helping these big companies keep track of the lifestyle of their consumers.

Big data analytics training is helping hospitals to make staffing decisions so that they have an adequate number of people available when the hospital is oozing with patients. Also, this helps in tracking the hospital supplies and inventories like local painkillers, surgical equipment, surgery wearables, etc. It keeps the whole ‘Hospital-Ecosystem’ in check. It also helps in tracking real-time information and providing feedback on patients’ health regularly thus making the job of a doctor pretty convenient. Big data has brought the whole healthcare industry on a digital platform where details such as the medical history of a particular patient can be figured out in a fraction of seconds.

How this data is used by the Government

The government uses this data to chalk out the healthcare strategy for a particular country it belongs to.  This data helps the government in figuring out the number of hospitals, medical supplies, etc. needed by its people. This data can also be used in educating people about the benefits they can avail in terms of health care and well-being.

Conclusion

The healthcare is growing and this growth is not going to stop anytime soon. Like all other industries, big data is driving this growth and transforming the healthcare industry into a whole new world thus improving the decision making process and optimization of costs.

How Do A Big Data Help In The Insurance Sector?

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Understanding Big Data

The concept of information is power puts data into the center of progress, data today is the real deal. How exactly to put together the concept of big data? Well, the name is very suggestive and builds a clear picture as to what it could be.

Big data can be understood as a big, complex & voluminous database that contains a variety of information regarding everything and anything that generates some kind of information. The data sources are ever-growing and the velocity of data from these data points is magnanimous, adding tons of data every second to this existing large database called the Big Data.

So what’s the use of collecting this data from every source available? In the digital age, we are consuming a huge amount of data on a daily basis, courtesy of the internet. Whatever we search on google is available because somebody tried to store it and upload it for the use of masses.

Now while using the internet we don’t just consume the existing data but create new data sets which could be in the form of anything ranging from our names, contacts to our web history. The three V’s important to the formation of the big data are Velocity, Volume, and Variety.

Why fuss over the big data? Well because the big corporations are ready to kill for it! Big data provides much-needed insights into customer preferences and their data history which can help them inefficient targeting of customers and better their sales and marketing revenue.

Big data scientists gather specific information and the technical know-how while preparing to enter the industry of data science, they use big data for providing valuable insights to the firm. The big data analytics training has helped boost the career prospects of people from the IT space. One of the reliable programs is the big data Hadoop training course which is curated by Hadoop industry experts.

Implications in the Insurance industry

If you had the power to predict something with high probability on the basis of the past track records wouldn’t it be fruitful? That’s how big data help every industry in general that needs a past track record to implement changes in the future functioning. Broadly, insurance ranges from general to automobile & healthcare which is further broken down into sub-segments depending upon the industry.

The most obvious use of big data in insurance is customer insights based on the information gathered from the customer since this is a generic one applicable to every industry it’s easily understood. Let’s take an example of the automobile insurance so the information relevant to pricing the insurance policy premiums and add-ons depends on various factors like safety level in the buyer’s vicinity to their historical driving record. The insurance firm can accordingly charge different buyers with different rates as the degree of safety is very subjective and also the driving habits of people vary.

Where do insurance companies fail? If you go in a little deeper into the subject you’ll find that the level of fraud related to an insurance claim is paramount resulting in loss to insurance providers. Now the case of moral hazards is very prevalent and people often see insurance as a total safety net so they don’t even bother to maintain a minimum safety standard.

Big data steps in to identify a probable false claim based on the history of the party claiming an insurance amount, the level of fraud has come down drastically owing to big data in insurance.

What all can go wrong for any particular scenario of insurance? These scenarios are also developed with the boon of big data. This helps in better premium pricing and reduce the chances of a surprising claim for unaccounted factors.

Conclusion

The term big data is very suggestive of the work it performs and what it holds in its reals. Containing the massive amount of databases from each and every data point, big data paves the way for future based on the historical records of things. Among the numerous applications of the big data, the Insurance industry seems to be gaining a whole lot from the insights that this mammoth entails. From reducing the cases of insurance fraud to pricing the premiums of various insurance policies given the subjectivity of the user, the big data is shaping the insurance industry for a better future and better profitability.

What are the Use Cases of Big Data in Real Estate?

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Catching up on big data & real estate

Real estate is comprised of assets such as property, land, houses, and buildings. Real estate is a budding sector where properties are dealt with every now and then. Real estate agents facilitate the buying and selling of homes, land, etc. on the behalf of the parties whose interests are vested in it.

Big data is a common term that is widely accepted for large sets of data which is analyzed using various computer software to bring out trends and other insights to understand consumer behavior and several other aspects of the economy.

How is big data related to real estate?

Big data has transformed the way data is perceived these days. It has facilitated a smooth analysis of data and the extraction of vital information. Real estate involves a huge client base thus involving a huge amount of data. There are buyers, sellers, financial institutions and a lot of other parties who require data chunks to cater to their specialization.

Real estate is moving to an electronic mode thus becoming more data-centric. People are buying and selling properties using mobile platforms thus collecting huge amounts of data. The real estate agents through these application data can easily get to know about the properties which are in huge demand and thus control the rates of the already volatile market.

Real estate should have hands-on big data so that they can reap out the benefits of the huge data resource available. Buyers are moving to a mobile platform where they can assess various property options at the same time and improve their search experience. Realtors will also know their clients better and serve them in accordance with their needs. This data is really valuable.

The biggest challenge in the real estate industry is that technology touches this sector at a very slow pace but the roots of technology are growing so fast that the real estate sector has also got a good taste of it.

Influence of big data in the real estate sector

Big data plays a real role in fixing the prices of tangible properties. Also, people who have an intention to buy get to know about the prevailing market rates. The realtors can analyze the cash flows which can take place in the future on the basis of demand. When an interested party visits a real estate website he knows what he is searching for. He has his specific parameters in place thus giving the app controller user-specific data.

The big data analytics training the realtors with a lot of information about an individual such as his age, region to which he belongs, what kind of house does he require, etc.

Such information helps the realtors to make notifications and emails more personalized thus winning the trust of the consumers. Big data also gives an insight into people who are interested in taking properties on rent. These real estate giants have access to a database of millions of people.

With the help of big data, real estate companies are able to market their products efficiently and smartly. Big data is being used by the realtors in marketing their products and also reaching their prospective clients with the help of various marketing campaigns such as email marketing, influencer marketing, celebrity marketing, etc.

Big data also helps in improving the decision-making process for these companies and also for the individuals who are visiting the application. With a plethora of options available, an individual could get all sorts of information on a particular house such as the locality it is in, how old the property is, how far the market is and so on.

Conclusion

This shift in the outlook of real estate businesses has just begun. The more these companies analyze the data available, the more it becomes lucrative. The process of implementation of big data in the dynamics of real estate business is a little slow but all good things take time. Also, they have already started to make the best out of the data available by slowly unwinding the treasures hidden in the layers of the so-called complex data.

How To Encourage Your Children To Learn About Big Data And Modern Technologies?

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How To Encourage Your Children To Learn About Big Data And Modern Technologies?

Phrases like Deep Learning, Neural networks, Machine Learning or Artificial Intelligence can be a big put-off for those parents who get easily overwhelmed by the changes in digital technology which seems to change minute-by-minute. The exponential growth of data is powering it and big data analytics courses are fast becoming essential.

This is what your children inherit and grow up in. It is crucial to have them trained early on if they need to be technologically equipped to handle their daily lives and become contributors to the growth of both the economy and society at large. There is no dearth of the ignorant in places of power who have no clue regarding the present technology let alone the future technologies that are already happening!

Every country has its share of shame and court cases on the misuse of technology which stems for a complete lack of understanding of the underlying science and principles of technology. You can change that and we shall look at certain pointers that can help you along to make the future of your kids in big data analytics courses an educated and well-equipped one.

Understanding the basics:

Kids understand concepts very easily if the examples are right. Just as they learn to walk, talk in any language, and interact with others based on their experiences of watching and doing, so also complicated concepts are simpler to explain than you may think. After all, technology has existed over generations and it is those who learned to question early that became the next generation’s Einstien or Newton.

Your involvement is vital:

One of the easiest ways to update your knowledge would be to get involved in your child’s learning. Parents are the role model on which the child bases his/her behavior. Taking an interest in the learning data analysis and how modern technology will not only help you explain the simple concepts of Deep Learning, Neural networks, Machine Learning or Artificial Intelligence but will also help you understand better and make better choices as technologies advance. Ex: Buying a smartphone today involves understanding what they can do for you with Google Assistant or Amazon’s Alexa. Go ahead and discover your gadgets.

Rewards are motivators:

The simple science of getting kids to thrive in their learning is to create a task list and reward the completion of tasks with simple child-friendly rewards like a party, movie, or treat of their choice. Starting such a system helps them inculcate discipline, cleanliness, and innovation in thinking through their tasks. Rather than play for hours on end, kids find it more interesting to learn to handle gadgets like the computer, smartphones or home theatre. They not only feel grown-up but also start skilling themselves early.

Use authentic training resources:

Teaching children to Google their questions opens up Pandora’s box when un-monitored. However, the internet has some very interesting videos on YouTube, simple beginner’s courses depending on the age of your child, websites for learning kids, games that explain concepts behind what appears complicated technology and child-friendly apps that are invaluable for both you and your kids. Why not consider a few big data analytics courses online?

Learn from mistakes:

Part of the learning lies in its being used and that’s where mistakes are bound to happen. Just like kids fall and learn to walk better, complicated subjects will come with mistakes and errors that should be treated as part of the process. The parent’s role in encouraging and handling rejection due to mistakes is just the same as in subjects like mathematics, science or any other. Just as long as the child enjoys the process and no stress is created they will learn if you are sensible about their failures.

Get Assistance:

Rather than venture into the unknown territory alone, there are ample resources that you can exploit to teach your children such as teachers, tutors, and short-term beginner courses at colleges that can help. Scour your neighbourhood for students who have done big data analytics courses and would be willing to orient your kid for a very reasonable hourly fee while keeping them well-attended to and busy learning something new.

Parting notes:

So, how can proactive parents encourage children to acquire knowledge and skills in big data and modern technologies? Well, the answer is simple. It is all about the training of the mind to form a basic skill set that is curious and learns by itself. At Imarticus Learning you can learn and also enrol your children in professional courses like big data analytics courses that help build appropriate skills in the field of emerging technology. You will be getting them a quick start in their careers that could prove invaluable in time.

What Are An Interesting Careers To Explore In Big Data?

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What Are An Interesting Careers To Explore In Big Data?

Big Data is no longer a future capability but is already in use in a variety of sectors and industries. Some of the uses are as diverse as taxis in Sweden using data to cut back on traffic and emissions to Barcelona building a smart city based on data and farmers worldwide using data to reinvent farms. The benefits of Big Data applications and data-driven strategies have thrown open the doors to a variety of careers which are satisfying, always in demand and pay very well.

Doing a big data course is one of the best options to hone your skills on the current demands of the emerging technologies in Big Data and allied fields like machine learning, artificial intelligence, deep learning, and neural networks among others.

Let us explore the top careers and the requirements to make a career in this lucrative area. Salaries are as reported in Payscale.

  • DATA SCIENTIST: These are the experts who produce meaningful insights and work with Big Data volumes using their technical and analytical skills to clean, parse and prepare data sets from which an analyst can apply algorithms to get business insights. Their salary is in the range of 65,000 to110,000 USD.
  • BIG DATA ENGINEER: These engineers evaluate, build, maintain, develop, and test big data solutions created by solutions architects. Their salaries lie between 100,000 to 165,000 USD.
  • DATA ENGINEER: The engineer is responsible for data architecture and the continuous data flow between applications and servers. Their salary range is 60,0945 to124,635USD.
  • ML- SCIENTIST: They work with adaptive systems and algorithm development and research. They explore Big Data and train the big data course to automatically extract trends and patterns used in demand forecasting and product suggestions. The average ML scientist’s salary is 78,857 to124,597 USD.
  • DEVELOPER-DATA VISUALIZATION: These people are responsible for the development, design, and production of interactive data-visualizations. They are the artists who bring to life reusable graphic/data visualizations. Their technical expertise is valued and the salary range is 108,000 to130,000 USD.
  • SPECIALIST- BUSINESS ANALYTICS: This specialist assists in testing, supports various activities, performs research in business issues, develops cost-effective solutions and develops test scripts. Their salary range is 50,861to 94,209 USD.
  • BI- ENGINEER: These engineers have business intelligence data analysis expertise and set up queries, reporting tools etc while maintaining the data warehouses. Their expertise earns salaries in the range of 96,710 to138,591 USD.
  • SOLUTION ARCHITECT- BI: These architects deal with solutions that aid sensitive timely decisions for businesses. The salary range for this role is 107,000 to162,000 USD.
  • SPECIALIST- BI: These people also are from the BI area and support the framework across the enterprise. The salary range for these is in the range of 77,969 to128,337 USD.
  • ML ENGINEER: This important aspect of ML develops solutions aiding machines to self-learn and autonomously run without human supervision. ML engineer’s draw a salary of 96,710 to138,591 USD.
  • ANALYTICS MANAGER: This manager deals with the design, configuration, support and implementation of analysis tools and solutions from huge transaction volumes. Their salary range is 83,910 to134,943 USD.
  • STATISTICIAN: These people are tasked with gathering, displaying and organizing numerical data used to make predictions and spot trends. The salary range for this role is 57,000 to 80,110 USD.

The skills required:

The basic attributes required for these jobs is:

  • Knowledge of Apache Hadoop, NoSQL, SQL, Spark, and other general-purpose programming languages.
  • Skills honed in a regular big data analytics course.
  • Adept in ML, data mining, quantitative analysis, data visualization and statistical inferences.
  • Personality attributes like being a team player who is adroit in creative and analytical thinking, innovative approaches and creative problem-solving.

The importance of certifications: 

Certifications endorse your skills and validate that you have the knowledge to practically apply your skills. Certifications in the below subjects will stand you in good stead when at interviews and improve your career prospects. Do go in for certifications in

  • Hadoop, SAS
  • Microsoft Excel
  • Python, R, and the Java suite
  • Pandas, MongoDB
  • Apache Spark, Scala, Storm, Cassandra, etc
  • MapReduce, Cloudera, and HBase
  • Pig, Flume, Hive, and Zookeeper.

Parting notes:

It is best to do the big data course at Imarticus Learning as they train you to be career-ready with skills on the latest technologies like the ones mentioned above. Their certification is well-accepted in the industry. So, why wait? Start on your career journey today!