How Data Science is Taking over the Market

DS-case-study

Data science is a part of the data industry. Data is mainly information that is stored or processed in computer systems. Data is processed by the CPU of a computer and stored in files and folders on the computer’s storage devices. Data stores as binary data only in ones and zeros. Data science means the study of data in large amounts. Developing methods of recording data. Storing data and analyzing data effectively to extract useful information together all of this is data science. It is a separate field of computer science. In computer science, when something to store, record, or process data after creating programs or applying algorithms and data analysis comes to work. Data science is more related to statistics which is a sector of mathematics. And also that includes presentation, collection, and organization of data. Most of the industrial companies hire a data science engineer or give data to a data science company to work on that.


Uses of Data Science in big amount -


  • Spotify has around 124 million free and 108 million paid users. They are using many advanced Data Science and Machine Learning techniques to extract insights of user data to achieve the main goal of their business model.

  • About 1.2 million people upload 136,000 photos and update 293,000 status globally in a minute. They are also using advanced Data science technology to process huge data amounts which is counted 500 terabytes by Facebook.

  • Uber is established already in 449 cities across 66 countries. Uber is running over millions of users and managing 1 billion rides. To process this huge amount of data is processed by advanced data science techniques.

  • Netflix is using Big Data to get More engagements on their streaming platform. Around 50 countries have netflix access and about 54 million users all over. Netflix do process their users data for recommendation and many other uses.

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    There are many subsets of data science in the modern world. Those are more likely related to computer science. Like data mining, big data, database, and so on. If a company has petabytes of stored data they have to use data science to develop an effective way to manage those data for further read and write. Data science covers the entire scope of processing and collecting data in a large amount.


    Data science often confuses people with its own subset, Data mining. Data mining is a process of analyzing huge amounts of data to discover patterns and other information which is mainly performed on databases. Data is stored in a structured way while mining. By mining large amounts of data one can discover the hidden and undiscovered information and use that for other purposes. The tech giants like Google and Facebook also use data mining technology to process data for further uses.


    Big data is often used at the industrial level for analyzing and processing. It used to process or mine a specific amount of data which rather can not be stored or processed by using traditional database softwares. Google and Facebook also use the technology, They divide the large data into many specific groups and mine them as Big data. Big data solves the problem of using Access databases or DBMS. Those can only store or process respectively gigabytes and petabytes or exabytes of data but can’t process that much. Some of the popular Big data softwares are Apache Hadoop, IBM’s Big data platform, Oracle NoSQL database, Microsoft HDInsight, and EMC pivotal One.


    Data management is also an important part of data science. Data design, Data storage, Data security, etc. are the subsets of data management. Among them data security is a very strong thing that must be handled. Any individuals or businesses store their valuable data on computer systems. Then it is very important to protect those data that could be dangerous for a business or individuals if data leaks. To make asure of the privacy and integrity of their data they must take steps to install a firewall to prevent unauthorized access to your computer. Encrypting data for cloud storage is very effective nowadays. So, every individual or businesses should use data management for safety or data analysis.


    Data analysis is important for every enterprise to process and compute their data and also be stored securely. Just try Data Science and get more effective and useful information extracting data.


    We can provide some great Data management Services to you.

    We at Superior Data Science can analyse the data of your organization to make an effective decision based on the forecasting done by using AI and machine learning techniques.


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    Advantages of Machine Learning in Financial Forecasting

    Using AI to robotize the monetary estimating measure presents a few remarkable advantages for senior money heads and their groups. The key advantages are summed up beneath.

    1. Capacity to Produce More Accurate Forecasts, Faster

    As referenced before, AI empowered estimating can free monetary gauging of the concentrated work of gathering and accommodating information. The apparatuses can be designed to gather and accommodate extremely enormous informational indexes in a mechanized style. In addition, AI apparatuses can assist with deciding business drivers and enormously diminish estimate blunder. AI calculations are intended to gain from the information after some time and foresee which drivers have the best effect on monetary execution. After some time, the model turns out to be more precise and produces figures all the more rapidly.

    2. Hedge between best and worst case scenario

    With accounting page driven gauging measures, there are cutoff points to the number of information sources and how much information can be processed and burned-through inside anticipating models. AI devices can significantly upgrade the volume and sorts of information that can be utilized on the grounds that the apparatuses can hold more information and process it quicker than people. Through this way we can have the better chance to hedge between the best and worst case scenario.

    3. Empowering Value-Adding Activities

    Customary estimating measures ordinarily expect examiners to invest the vast majority of their energy accommodating and gathering information as opposed to chipping away at esteem added investigation and collaborating with the business. Utilizing an AI answer for production at any rate a standard estimate can help investigators move away from these commonplace assignments and spotlight on understanding operational drivers, key business occasions, and microeconomic and macroeconomic elements that may affect the business, carrying those experiences into the determining cycle. Utilizing AI can eventually help monetary investigators accomplice all the more intimately with the business and backing dynamic.

    The Emergence of AI in Accounting and Finance

    There are sure businesses that are generally helpless to the effects of AI. The most referred to report from NPR predicts that:

    • Bookkeepers have a 97.6 percent possibility of seeing their positions computerized.
    • Accountants and examiners have a 93.5 percent possibility of seeing their positions mechanized.
    • Financial examiners have a 23.3 percent possibility of seeing their positions mechanized.

    To summarize, occupations that are comprised of repeatable, precise errands have higher danger of being mechanized than those that require judgment, examination, and relationship building abilities. Thus, in the event that your present place of employment regularly expects you to show those attributes, at that point you need not concern. For Finance and Accounting, AI and robotization are viewed as suitable answers for successfully managing consistency and danger challenges across different areas. To stay serious, organizations are moving from work exchange and seaward unrest to mechanization insurgency. Man-made intelligence speaks to an occasion to decrease the weight on money experts, especially around conventional monetary exercises, for example, exchange handling, review and consistency. These exercises in their present structure keep money from being more essential colleagues.

    In what way Might We Help You Improve Your Customer Service with an Advanced Platform?

    • Build ai platform for your team
    • Quick financial projections according to your double entries
    • Analysis Charts and plots
    • Resources to carry on this project
    • Superior Data Science builds reinforcement learning agent

    Through our platform you will be able to get the forecasted financial statements including income statement, balance sheet, cash flow statement. On these forecasts you can have the opportunity to decide and take actions on.best and worst case scenario. Throught the forecasted data organization can take actions to create value for their investors.