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Tag: Big Data Analytics certification

Understanding the Role of Data Analytics for E-Commerce Success!

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The demand for data analytics in e-commerce is on the rise. Data analytics is a key tool for understanding the behavior of your customers and prospects, allowing you to make data-driven decisions. Data specialists have a promising future in this industry, and companies are clamoring to find talented individuals who can help them better understand their consumers’ desires.

The increased use of data analytics will be pivotal for businesses that want to stay competitive in today’s marketplace. This blog post will discuss how data analytics can help e-commerce businesses succeed in today’s competitive marketplace.

Role of Data Analytics in E-commerce Success

Data analytics plays an increasing role in e-commerce success. Companies are looking for data analysts with the skills to help them gain a competitive advantage by understanding customer needs, behaviors, and trends within their industry. More specifically, companies rely on data analytics professionals to find:

  • Targeted customers that they would not have reached otherwise
  • Deep insights into areas such as product development and merchandising
  • Actionable information on factors such as click rates or session times across devices (desktop vs. mobile) can be used to improve online conversion rates

In addition, these new positions require individuals who can communicate effectively throughout a company’s hierarchy—from senior management down to marketing teams—to ensure all stakeholders have access to the information they need to make informed decisions.

Data is also playing an increasing role in offline commerce. The challenge of understanding customer behavior across channels has led to the increased demand for data analysts with a comprehensive view of all aspects, including brick-and-mortar retail and online sales and promotional efforts.

A growing number of companies are seeking specialists who can collect, cleanse, manage and analyze large amounts of disparate datasets at scale, helping them gain insights about their customers that were previously hidden or difficult to address.

Companies have access to more sources than ever before—from internal company databases such as CRM systems (customer relationship management) and ERP systems (enterprise planning) through social media platforms such as Facebook or Twitter. In addition, companies are finding new ways to interact with their customers and gather data through mobile apps and other interactive tools that enable them to obtain information about customer preferences (e.g., location) in real-time.

What kind of skills are required to succeed as a data specialist?

For a successful data analyst, it is important to have strong analytical skills. You need to ask the right questions and then find and understand relevant information (data). Some of the other qualities that are needed include:

  • Ability to work with large datasets
  • Attention to details
  • Analytical thinking rather than creative thinking
  • Ability to identify patterns
  • In-depth knowledge of statistical concepts like standard deviation, correlation, and regression analysis.

Have a promising data specialists career with Imarticus Learning

Big data analytics courses in IndiaImarticus Learning offers a data analytics certification course that prepares you for a high-growth career. Our unique combination of analytics courses helps students build strong foundational skills and practical industry exposure to build a successful career in the field of Data Science and Business Intelligence.

This course is developed and taught by industry experts with significant experience in analytics. It includes a range of topics, from basic statistics & probability theory to advanced machine learning techniques. This course will help you move forward in your career!

For more details, contact us through the Live Chat Support system or visit any of our training centers based in – Chennai, Mumbai, Thane, Pune, Bengaluru Hyderabad, Delhi, and Gurgaon

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.

Is Big Data The Key To Curing The NHS?

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Is Big Data The Key To Curing The NHS?

The essential and key aspect of every developed nation-state is access to better healthcare facilities. In a dwindling mass of third-world countries, we often find that poor healthcare affects the economic resources that remain untapped for a long. The National Healthcare system developed in the United Kingdom in the aftermath of World War 2 was the most progressive decision undertaken by the state and sovereignty for its citizens and that protects them till today.

This healthcare system can also be accessed by international citizens who stay in these places for a short period of time owing to various reasons. Since its establishment in the early 1950s, it has facilitated an increase in the life expectancy of people. However, handling such large amounts of patient records can be extremely gruesome and challenging especially with the late detection of many diseases the NHS has of late been suffering from a series of major losses. It can, however, be avoided with the emerging technological renovations happening all over the space, especially with the emergence of Big Data.

Big data training helps in involving and combining unstructured databases with a structured database and helps in providing the best solutions to the data barriers with its system of integrating, transforming and empowering the services.

The benefits of big data are clear, and it has become much easier for organizations to collect and store this level of data from their customers and stakeholders. The challenge is to convert that data into information that can help improve operations. For the NHS, its test run operations in Scotland have helped in not just collecting data but also implementing the analysis techniques to understand the warning signs of various new diseases. This targeted intervention can help the NHS from not just run into deficits but also save many more lives.

However, this intervention has to be systematically curated and the needs of the organization addressed effectively to overcome the barriers that exist in the implementation of data analytics. These businesses provide solutions in the market that can cater to almost all niche business operations and ensure that the products and services provided by them are catered effectively.

The predictive data analytics helps in providing a potential light on the patient flow and hospital demands and allows the NHS to make informed decision-making. It helps in allocating the NHS appropriate resources and improving its time efficiencies.

But there also exists a barrier to the implementation process. The big data analysis is seamless but requires huge investment, especially in cases of NHS where a large amount of information has to be provided and the IT infrastructure and data have to be organized to ensure the flow within the business.

Therefore, utilizing this big data across the organization needs to be balanced with an effective training process for the staff to work with these technological assessments. This data also has to be regulated and protected to avoid any mishappenings. It will require initially huge financial investments and operational changes and trained staff to handle the situation at times of crisis.

Therefore, what we have to look at now is whether this system is effective and can it really change the dynamics of healthcare in its absoluteness. Arguably we could say that the investment process is too difficult considering the present scenario of the market systems and the long-term potential to drive down costs across the NHS. However, in today’s world, technological means have the potential to save a company from going into bad daylight and bring about a revolution in the system process and ensure that the healthcare system can become really effective in the long run.

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.

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.

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!

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.

What are The Different Fields in Data Analytics?

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One of the most popular technology-empowered jobs out there, data analytics consists of various disciplines in the field of data science. There are plenty of different areas in which data analytics is applied, with the banking sector being the foremost. As the world starts adopting data analytics techniques, there are different jobs that are present in the field of data analytics.

Here are four of the main fields in the data analytics sector:
1.Data analyst:
Some companies use the terms “data scientist” and “data analyst” interchangeably. Data analysts generally work with SQL databases and pull data out of the same. The job also entails becoming a master of Tableau and Excel and occasionally analyze results of A/B testing and leading the Google Analytics account. Other roles can also include reporting dashboard data and producing data visualizations.
2.Data Engineer:
Data engineers are generally bought in when companies start getting a lot of traffic and need someone to set up the infrastructure to move forward. There’s also a need for somebody to provide constant analysis and this job can generally be posted under “Data Scientists” or “Data Engineers” as well.
Data engineers require a decent knowledge of machine learning, and heavy statistics as these are one of the main assets companies look for when they’re starting out themselves. Software engineering skills are seen as more of a secondary requirement during the initial phase. Data engineers generally get to own all their work but won’t have much guidance and could reach a point of stagnation.
3.Machine Learning Engineer:
There are many companies where data ends up being their main product. Data analysts or machine learning will be a huge part of their internal processes here. A machine learning engineer who has an education in statistics, physics or mathematics will have a bigger role in these situations. If they’re looking at continuing in an academic path even afterward, then this is a great role to fulfill.
Most companies which look out for machine learning engineers are consumer-facing and have huge data which they offer out to other companies.
4.Data science generalist:
Companies look for data science generalists to join other data scientists internally. Companies that take interview care about data but aren’t necessarily a data company themselves. They will be on the lookout for individuals who can work on a wide variety of hats, including touch production code, analysis, data visualization and more.
Data science generalists are sought after to fulfill any specific niche which a company feels their team lacks. This can include areas such as machine learning or data visualization for example.
Thus, it’s important that you’re always on the lookout for a job that satisfied your skill set the best. There are so many options available for those interested, and with data analytics shaping the world we live in, it will serve you well if you can find your own niche.
Join Imarticus to get the best in big data analytics courses and fast forward your career graph in the field of data science. We offer data analytics at our centers in Thane, Pune, Bangalore, Chennai, Hyderabad, Coimbatore, Delhi.