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Tag: analytics and artificial intelligence training

How Do I Start a Data Analytics Study?

Posted on by Imarticus Learning

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.

How is Big Data Analytics Used For Stock Market Trading?

Posted on by Imarticus Learning

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.