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Tag: big data

With Jobs at Risk, can a Career in Big Data Keep You Safe?

Posted on by Imarticus

Data powers the information economy just like oil powers industrial economy. No wonder they say, “data is the new oil”. A critical asset to many industries, data science and AI changed the way information is gathered and processed. Even when COVID-19 hit the global economy, leading to job cuts and hiring freeze, data science remained unaffected.

While companies do not debate on the importance of data science, collecting and storing the huge volume of data was a big challenge. With limited capabilities, companies had a big struggle to maintain and process data. However, AI and cloud-based technologies provide a solution to this problem. These technologies have created better job opportunities for data professionals than ever before. If you are aspiring for a data analyst career, there isn’t a better time than this.

Why Big Data?

The world is consumer-centric and will remain so despite the hard hits on the economy. Consumerism is the driving force that creates revenue, and job opportunities. From healthcare to e-commerce, all industries are data-driven. The data requirement changes from one business to another, from one company to another. But the enormous amount of unstructured data can be collected using various tools and techniques, organized and structured according to the business needs.

No matter the business is consumer data is vital to all businesses. The tech giants like Google, Amazon etc, and the social media giants like Facebook have been using the potential of data to achieve a competitive advantage over their rivals. And the result is pretty much evident. They are far ahead of their competitors.

What is common among all of them is that they collect large swathes of data regarding their customers – right from what products they buy, which products they ditched after adding to the cart, which posts get better engagement, how long does a person spend time on their webpages – every single move of their customer after arriving on their website is tracked, processed and analyzed to make better business decisions.

The global health crisis saw the extensive application of data, how it can be used to manage a crisis better. From contact tracing, health screening and mitigating the spread. Many apps were developed to help contain the spread, leveraging the GPS to identify the COVID-19 hotspots.

The Increasing Demand for Data Scientists

COVID-19 has indeed changed the way the world functions. With more people staying indoors, individuals flocking the internet also increased. From work to shopping, everything is being done online. And this has increased the requirements for data scientists. While many companies struggle to acclimatize and manage their current employees logging in from a remote place, Tech firms are out with a pressing need to recruit more talents.

With more students and professionals active online, the need for online tools and platforms is growing, and this has led to the demand for an intense expansion of their talent pool.

AI and cybersecurity talents are the most coveted as many companies need technical support in digitizing their businesses. This calls for the improvement of data security measures and to enhance automation to reduce the on-site manpower.

Firms that rely on AI-powered software and those which provide such platforms are on a lookout for technical talents including software engineers and data analysts. Furthermore, financial services companies are also gearing up to become market-ready when the economy reopens. They have started headhunting for people with risk management and data analytics skills to cater to the recent spike in digital banking and online payments activities.

Data Science Online CourseData science is one of those areas not affected by COVID-19. In fact, the pandemic and the enforced stay-ins have resulted in an increased demand for data scientists. If you are a new graduate, take this opportunity to make the most out of the current market situation.

Enrolling in a Big Data Analytics Course could help you land on a lucrative career in data analytics and big data.

Data Science Job Opportunities Continue to Surge in 2022!

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Data science has revolutionized the functioning of almost all industries in the world today. The creation of data is the highest at the moment due to the widespread process of digitisation. Therefore data science tools and technological advancements are being deployed in order to push further productivity amidst all organizations.

With this, there is the provision of Big Data, Machine Learning, Data Analytics, Data Mining and Data Analysis thus creating large importance for this technological field.

All businesses and organizations require efficient and quick problem-solving methods. This is offered by data technology, having the ability to analyze and comprehend large sets of data in order to resolve a variety of problems in a fast-paced and accurate manner. This is a much more sought after a method as compared to the completely engineered solution.

The development of proficient machine language algorithms and a change of direction from analytics that were descriptive has resulted in driving progress. Predictive analytics and maintenance have slowly been gaining popularity amongst industries and this popularity only seems to be growing.

Data Science JobsThe demands for various data science services have been seeing a large surge all over the world as researchers for the market predict its magnification in the near future. Due to this increased demand, the path for various other talents and job aspirants is clearing. This would allow them to try their hand and work hard while in this genre of work. The vast number of technologies in relation to data are creating large opportunities for up and coming data professionals to seize.

With an estimated increase of over 1 lakh new job openings in the present year of 2020, which is a little more than a 60% increase from the previous year (2020), aspirants have a large number of openings to prove themselves with a data science career. Almost 70% out of these job opportunities are for budding professionals with experience less than or up to five years.

In a bid to remain in the fast-paced competition of today’s market and maintain relevancy, organizations, businesses and various other companies are taking up newly emerging technology. Due to a large amount of data that is being created, data technology and science is the answer to mining insights that are actionable for businesses.

There is thus a very large scope in this field for data science professionals set in the present year, 2022. This year has been the best year for Data science and furthering its opportunities.

Industries of energy, pharmacology, healthcare, media, retail, e-commerce, etc. are creating a large number of job opportunities in the field with average potential salaries going from 10 lakhs to even 14 lakhs per year.

The industry of data science had been previously (2022) facing a large shortage of skilled professionals which have increased in large numbers this year (2023).

By taking a data science course aspirants will be well equipped with all the necessary information in order to succeed in their future data science career.

The Top Data Analytics Certifications in 2020 For Advanced Data Expertise!

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The explosion of interest in technologies such as the Internet of Things (IoT), Big Data and Artificial Intelligence (AI) has stepped up demand for data scientists and analysts over the past few years.

Advanced capabilities in data analytics are just too critical to ignore at this point. In a matter of years, they’ve reached out from a niche sector to nearly every industry that generates any form of data. However, data analysts with the right mix of skills, experience and spirit of innovation are quite rare. This means businesses are well away from realizing the true potential of their data dumps and the insights that can be garnered from it.

Big Data Analytics Certification CoursesIf you’re interested in pursuing data analytics jobs sometime in the future, it is advised that sign up for big data analytics training opportunities within or through your company. If you’re a student or a fresh graduate, enrolling in a Data Analytics Certification Course is a sure-fire way to strengthen your core competencies and upgrade your skillset in the process.

Here are some of the top data analytics certifications you could choose from in 2020:

  • SAS Certified Data Scientist

To earn the SAS Certified Data Scientist certificate, you will need to pass all 5 SAS Certified Big Data Professional and SAS Certified Advanced Analytics Professional levels. They consist of two and three exams respectively. The exams test a student’s knowledge in big data preparation, programming, statistics, predictive modelling, text analytics and visual exploration.

Upon completing the exams successfully, the newly-certified professional can gain insights from big data using SAS tools as well as open-source options. The professional will also be skilled in creating machine learning business models to derive insights and influence decisions at a higher management level.

  • Microsoft CSE (Certified Solutions Expert)

This certification deals with data management and analytics. It consists of 12 exams; however, aspirants will first need to earn at least one out of the seven MSCA (Microsoft Certified Solutions Associate) certifications. The costs of the exams don’t include the training material, which a candidate can source directly from Microsoft.

This certification prepares you for building data solutions at an enterprise level and applying Business Intelligence approaches to big data. It also prepares you for the administration of SQL databases. After obtaining this certification, job roles such as database analyst, BI analyst and database designer are well within your reach.

  • IBM Data Science Professional

This beginner-level certification demonstrates the skills of an individual in the subjects of data science such as SQL, Python, data analysis, basic methodologies and open source libraries. The candidate will need to complete nine courses spread out over 12 hours per week for a total of three months. These courses will include practical experiments and assignments that contribute to the individual’s portfolio. The professional certificate earned at the end of the courses is branded with the IBM logo and add weight to any data science-oriented resume.

  • Cloudera Certified Associate Data Analyst (CCA)

The CCA certification requires that candidates pass the CCA159 Data Analyst exam, which is a set of 8 to 12 performance-heavy tasks on the Cloudera Enterprise cluster. Each task is allotted 120 minutes and involves analysing a problem and coming up with a technical solution that covers all bases and is highly precise. The Data Analyst training course from Cloudera helps candidates prepare for this specific exam.

By successfully completing this exam, SQL developers will be able to demonstrate core competencies in Cloudera’s CDH setup through using Hive and Impala.

Conclusion

Data analytics allows industries to revolutionise their business operations and implement insights gained from sifting through previously unstructured big data. Data analysts with any of these certifications in their kitty can expect to rise to the top of the CV pile.

Edge Vs Cloud: Which Is Better For Data Analytics?

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What is Edge Computing?

Edge computing is a segregated topology which serves to bring processed information closer to the device that is gathering the data rather than relying on a central unit which would be located much farther away.

What is Cloud Computing?

Cloud computing involves the process of delivering important information and services such as storage without the need for involvement of active management.

Which Out of the Two Is Better For Data Analysis?

In today’s world where AI has become an extremely important part of our lives, developers are looking to merge the devices we use on a day-to-day basis with artificial intelligence to make running businesses easier for organizations.

In such cases, we must look at the various computing methods that can make this possible in an efficient manner. Here, you would think that cloud computing would hold an important position in making the most suitable and ideal decisions. Platforms which are based on cloud allow developers to quickly create, deploy and handle their applications.

These would include playing the role of a platform of data for applications, application development which would help bridge the gap between data and users, and so on. It is popular for its flexibility with data storage and the ability to perform analysis processes.

On the other hand, edge computing allows applications and various other analytical and service processes of data to be done away from a central data unit, bringing it nearer to end-users. It allows the processing to take place within the locally available resources, thus bringing it a step back from the intricately planned cloud model where data processing happens in specific data centres.

Let us dive into this further in detail.

Cloud vs Edge Computing: Latency Problems

Cloud computing is used extensively across various organizations and companies for data analysis. However, there may be situations where a business may face problems in collecting, transporting and analysing the data given.

Edge and cloud computing for Data AnalyticsWhen data is transferred to a remote cloud server, it allows the user to perform various complex algorithms with machine learning and thus predict the maintenance needs of a particular section. This is then forwarded to a dashboard on a personal system where one can determine what decisions are to be made further. This is all done comfortably from home or the office.

This is great, however, as one begins to increase the intensity of operations, one may begin to run into issues such as physical limitations on the bandwidth of the network and thus also latency issues.

Edge computing does a great job at reducing latency issues by involving a local server, maybe even on the device itself. The only difference here is that the issue with latency is solved at the expense of the processing power offered by cloud computing methods.

Businesses, with edge computing, are now being able to decrease data volumes which would need to be uploaded and stored in the cloud. This thus makes the process of data analysis less time-consuming.

Edge computing may still interact with other website applications and servers. It includes physical sensor thus allowing it to help run smarter algorithms and facilitate real-time processing which is used in smart vehicles, drones and smart appliances. It may not be as strong as a remote server, but it helps reduce the bandwidth strain that one would normally face with cloud computing.

Data Analytics CareerA big data analytics courses would help equip a person aspiring to work in the field of data analysis with all the information that would be necessary. A big data analytics career is a good option because it is an ever-expanding field with a large number of opportunities!

How Do I Start a Data Analytics Study?

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Before commencing anything new a lot of questions and queries baffle the mind. When starting a data analytics study there are some factors one must keep in mind for a smooth and practical flow of the study. By investing some of the time in the beginning to follow these steps, a good amount of time and efforts can be saved while carrying out the actual study.

Keep the following points in mind before kick-starting a data analytics study.

  1. Understanding the Capacity: Before you begin to explore a particular study in data analytics, it is significant that you know about the whole capacity of data analytics.
    Data Science Online Course
    There is going to be a great requirement of the theoretical knowledge and deep insight about data and understanding data. Learning about the coding languages and syntax is paramount to make a hold on data analytics.It can prove to be advantageous if you take up a data analytics course online which can make you learn data analytics and its different elements in a precise and detailed manner. You may refer to Imarticus learning which can help you hone your undiscovered skills and make you a genius in data analytics.
  2. Experimenting: Once you gain proper knowledge about the coding languages and their systematic usage, it is really important that before you jump on to the main data analytics study, you apply what you have learned by the way of an experiment. Internet is filled with data published by various renowned companies which can be used for the experimentation. Experimentation is the only means which can help you establish a relation between the cause and the effect.
  3. Specifying the Pre-requisites: Once you are done and satisfied with your experimentation, to begin the actual study in data analytics you need to specify the requirement of a specific date on which the research is going to be based. This data can be in any form like the number of people from the general population or the number of people working from home etc. Understanding the specifications of the data, in the beginning, is paramount.
  4. Collecting the Data: After specifying the requirements of data and recognizing the sources of that data, the collection has to be started. Data can be availed from various sources like the company portals or the organizational databases.The collection of data has to be appropriate and methodical so that it is not hard to decipher when the study begins. Sometimes the data collected is not at all in a usable manner and has to be filtered on various levels before beginning the actual study. In such a scenario, the data undergoes a processing and cleaning process.
  5. Processing the Data: For better understanding, scattered data has to be represented methodically for the study to be smooth. In this step, various tools are used to make the data workable. With the help of bar-graphs, tables with rows and columns, data are presented systematically. Generally, the use of spreadsheets is done for a structured display of data.
  6. Cleaning the Data: At this point, still, there would be a lot of information which is going to be of no use while carrying the study. There are chances that there is a duplication of the data. Most of the times there are certain errors in the data which may cause a lot of problems while studying and analyzing it. Such errors are got rid of in this cleaning process.

After following these steps, the study of data analytics can be taken forward in a hassle-free and smooth manner. To learn data analytics and how to communicate the data after analysing it, refer to Imarticus leaning which is an ideal way to learn data analytics through professionals.

Big Data Influences Online Trading in 3 Primary Ways!

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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.

Big Data influences online trading in 3 primary ways:

1. Levels the playing field to stabilize online trade

Big Data analytics

Algorithmic trading is the current trend in the financial world and machine learning helps computers to analyze at rapid speed.

The real-time picture that big data analytics provides gives the potential to improve investment opportunities for individuals and trading firms.

 

 

2. Estimation of outcomes and returns

Big Data AnalyticsAccess to big data helps to mitigate probable risks on online trading and making precise predictions.

Financial analytics helps to tie up principles that affect trends, pricing, and price behavior.

3. Improves machine learning and deliver accurate predictions

Big data analytics training can be used in combination with machine learning and this helps in making a decision based on logic than estimates and guesses.

Big Data Analytics

The data can be reviewed and applications can be developed to update information on a regular basis for making accurate predictions.

 

How Can Data Analytics Improve Remote Learning?

Posted on by Imarticus

Introduction

Data Analytics has transformed how we work today. It has brought in the automation we need. Big Data has found a lot of use in Industries like Healthcare, Finance, Retail, Real Estate, etc. It has made analysis and crunching of data a cakewalk. Earlier, analyzing and sorting information from data sets was a cumbersome task.

It required a lot of people and long working hours to analyse and extract information from those data sets. This got complicated as the amount of data increased and due to an increase in the number of data sets, the results were prone to errors.

Big data transformed and brought in a wave in the process with which companies handle data sets and data. Big Data and Data Analytics have not left any stone unturned.

They have even brought about a significant change in the education sector. It has become a hot career option and you can take up an online or an offline Big Data Analytics course to become a part of this transformation.

Data Analytics is creating new learning opportunities daily. It is now transforming the way students’ study and teachers teach. Data Analytics has elbowed its way to the pedagogy and is now setting up a new definition of how people study.

Remote Learning

Remote learning is the online way of studying where technology becomes the source or medium of knowledge exchange. Remote learning eliminates the use of traditional classrooms removing the barriers of place and time. The Internet has become an essential and Remote Learning is making the best use of it.

Big Data Analytics CourseRemote learning is now been done through a lot of platforms and mediums such as Video conferences, online tasks and assessments, discussion boards, webinars, etc. These platforms allow free flow of information and are equipped with all kinds of features like screen sharing, system control sharing, whiteboards, annotations etc. Remote learning is a new way of learning.

Remote learning generally translates to the face to face mode of studying using technological resources. You can initiate or have access to remote learning from the convenience of your homes.

Data Analytics and Remote Learning

Data Analytics has transformed the education industry. With a lot of data present, one can easily assess the demand for education and tap those markets. Big Data has made it possible for the education industry to move online.

A Data Analytics online training programme would give you insights on how things are working. Also, during a pandemic, the educators and school have easily moved to an online mode with the help of Big Data. With Data Analytics, the teachers can easily keep a tab on the performance of all the students. This would make use of different parameters to show conclusive results.

With Data Analytics, access to information has become easy. Also, the education system has been handled with a systematic approach and all the elements have now been automated.

These practices are now being standardised by trying different strategies and understanding what exactly would work in case of Remote Learning. Also, data analytics make learning safe.

Data Analytics make sure that the adoption of the system is done easily and also the students stay engaged. With data analytics, a lot of applications have been developed with simple and understandable user interface keeping in mind the demographics of the audience. Also, these applications take care of the safety of the student who is accessing remote learning resources.

Using Data Analytics, you can keep a tap on the activities of the students and how they are performing in class. It also manages attendance records, class files, etc with ease.

Conclusion

Big Data has brought about significant changes in the way students learn. With a little more up-gradation, Big Data will now drive this new model of education.

In The Face Of Job Uncertainty, Can A Career In Big Data Protect You?

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Big data involves extracting, analyzing and processing vast amounts of data using different techniques. With electronic apps proliferating through sectors and geographies, data is generated from various sources every day, everywhere, by everyone.

While big data entails sifting through unstructured data in multiple formats, the insights derived from these data dumps are invaluable to business or societal goals. Detailed knowledge of the business, through big data, will build greater efficiencies and give them an advantage over rivals in a data-driven environment.

The importance of big data has come further into light during the novel corona virus pandemic. Although the world is far away from a cure, the use of big data has allowed organisations and governments to manage the crisis, mitigate the impact as far as possible and maintain lock downs at a national level.

That said, healthcare is not the only sector that benefits from big data. Nearly every industry known to humans today can derive actionable benefits from big data, should they use it to its maximum potential.

The burning question, then, is if a big data career can keep you safe from job cuts, layoffs and furloughs. It just might, for the following reasons:

Big Data CareerA Shortage of Big Data Talent

Although there are many complexities involved in incorporating data-driven perspectives into traditional business practices, recruiting the best talent has become a consistent frustration across industries. Both as a result of this and as a precursor to this, companies have been failing to realise the full potential of big data and have been able to extract only a limited amount of insights.

A Breadth of Possibilities

Companies and industries are only just realizing the potential of big data across the board. Therefore, there is a myriad of paths to explore within the field in the coming year. This makes today an opportune time for those in looking to kickstart a big data career. Companies will be on the lookout for those with solid core competencies as well as a willingness to learn and experiment. Much of big data’s capabilities are hitherto undiscovered; big data analysts and scientists can help industries derive as much value as possible.

Evolving Technologies and Software

Technology continues to change and transform, which means new sources of data are being added into the mix. For traditionalists, this amount of data can look daunting and be misconstrued as useless. However, big data professionals can interpret these data dumps, extract value and engage in data storytelling such that big data drives business goals from the get-go. Additionally, new software is being introduced to handle niche requirements; a big data analyst or scientist with some experience in this will prove to be invaluable to a company exploring big data possibilities.

A Surge in Big Data Courses

If the number of enrollment in big data and related courses are anything to go by, then it is safe to say that interest in big data is only increasing by the day. A good big data analytics course, however, doesn’t stop just there.

It also delves into machine learning, Artificial Intelligence and Natural Language Processing because all of these are intrinsic to the process of deriving actionable insights. Any big data analyst worth their salt will strengthen their competencies in these fields first and then apply theory into practice.

Conclusion

A great way to get your foot in the door and strengthen your skillset is to enrol for a big data analytics course. While the job market seems to be bleak the face of a potential recession, you can offset some amount of impact if you’re pursuing a career in big data. It’s most likely to rebound from this depression and create meaning out of the noise even in difficult times.

Applications of Analytic Used in Ecom & Social Media Sites – #KnowledgeBytes | Imarticus Learning

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This Imarticus Learning video explains the Applications of Analytics. Amazon is one of the examples of applications of analytics. This video describes how Amazon has mastered the art of cross-selling by giving product recommendations on the right pages. This is possible because of the data analysis. Facebook is another example of analytics.

Facebook applies analytics to customize the notifications that the users receive. EA and Zynga from the gaming industry are other examples of the application of analytics. Another important application of analytics is the FICO credit score. Email spam filtering, which is a need for email applications, also uses analytics to give their users a better experience.

Check our complete #ImarticusPrograms playlist here: https://bit.ly/2JP52hM Subscribe to our channel to get video updates.

To know more about Data Analytics Certification, please visit here – https://imarticus.org/post-graduate-program-in-data-analytics/?utm_source=youtube&utm_medium=organic&utm_campaigntype=youtube

Why Imarticus?

Imarticus Learning offers a comprehensive range of professional Financial Services and Analytics programs that are designed to cater to an aspiring group of professionals who want a tailored program on making them career ready.

Our programs are driven by a constant need to be job relevant and stimulating, taking into consideration the dynamic nature of the Financial Services and Analytics market, and are taught by world-class professionals with specific domain expertise.

Headquartered in Mumbai, Imarticus has classroom and online delivery capabilities across India with dedicated centers located at Mumbai, Bangalore, Chennai, Pune, Hyderabad, Coimbatore, and Delhi.

For more information, please write back to us at info@imarticus.org Call us at IN: 1-800-267-7679 (toll-free)

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Febin George’s journey at Imarticus Learning – From Engineer To Data Analyst!

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It is a familiar experience for many of us – we study for one particular field, but then decide to pursue a career in another area of expertise. Febin George is accustomed to such a journey, having graduated as an engineer in 2015, only to then dream of becoming a data analyst one day.

Fortunately for him, he chose to join Imarticus Learning to develop his analytical skills and help him achieve his career in Data Analytics.

Before he had enrolled himself in Imarticus Learning’s Data Analytics course, Febin openly admits that he had little to no prior knowledge of what being a professional data analyst would entail. In essence, he was a blank slate when it came to the complexities of data science.

Now though, that is certainly no longer the case. Thanks to the comprehensive training he received at Imarticus Learning, Febin landed a job placement at M-Technologies Pvt. Ltd. as a full-time Data Analyst, something which he did not expect to happen so quickly.

Febin believes that only with the nurturing guidance of the profoundly experienced faculty members involved in Imarticus Learning’s Data Analytics course was he able to come so far in a relatively short period of time. His determination to further his understanding of data science was aided by the hands-on training he received on various modern-day analytical tools, big data concepts, and machine learning practices.

Having gained an intimate knowledge of data analyzing tools such as R, Python, and SAS from ever-helpful Imarticus professors during the Data Analytics course, as well as immensely beneficial industry insights from guest lecturers, Febin was able to rapidly developed his foundational understanding of the subject matter.

Going beyond the exhaustive course material on data analytics alone, Febin was also provided with much-needed soft skill training in order to polish his personality and prepare him to tackle tricky interviews in a distinguished manner. According to him, Imarticus Learning’s career assistance acts as a resume builder and makes a candidate far more appealing to prospective employers.

With the unwavering dedication of the Imarticus staff and the treasure chest of analytical knowledge he received from the Data Analytics course, not to mention his own drive, Febin George finally became the data analyst he dreamt of being. As he puts it, “Going for a data industry-specific interview requires knowledge on current trends, which is where Imarticus Learning really excels. I recommend Imarticus Learning to anyone seriously considering becoming a data analyst or scientist.”

To learn more about Febin George’s journey at Imarticus Learning, please click here.