IEEE Projects on Data Analytics

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IEEE Projects on Data Analytics, IEEE Data Analytics projects, IEEE Based Data Analytics projects, Data Analytics related IEEE Projects
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  • What is Data Analytics Project?

    Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions.Analysts may use robust statistical measurements to solve certain analytical problems. Hypothesis testing is used when a particular hypothesis about the true state of affairs is made by the analyst and data is gathered to determine whether that state of affairs is true or false

  • IEEE Projects on Data Science
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    Business analytics depends on sufficient volumes of high quality data. Data initially obtained must be processed or organised for analysis. For instance, these may involve placing data into rows and columns in a table format (i.e., structured data) for further analysis, such as within a spreadsheet or statistical softwar

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2019 IEEE Projects Based on Data Analytics

IEEE Projects on Data Analytics, IEEE Data Analytics projects, IEEE Based Data Analytics projects, Data Analytics related IEEE Projects

IEEE Data Analytics Projects 2019

How to do the Data Analytics Projects?
Data Analytics Concepts and Techniques
The consultants at McKinsey and Company named a technique for breaking a quantitative problem down into its component parts called the MECE principle. Each layer can be broken down into its components; each of the sub-components must be mutually exclusive of each other and collectively add up to the layer above them. The relationship is referred to as "Mutually Exclusive and Collectively Exhaustive" or MECE. For example, profit by definition can be broken down into total revenue and total cost. In turn, total revenue can be analyzed by its components, such as revenue of divisions A, B, and C (which are mutually exclusive of each other) and should add to the total revenue (collectively exhaustive).


2018-2019 IEEE Projects on Data Mining Contact: 9591912372

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Mini Projects on Data Analytics

data problems can also be identified through a variety of analytical techniques. For example, with financial information,IEEE Projects on Data Analytics the totals for particular variables may be compared against separately published numbers believed to be reliable. Unusual amounts above or below pre-determined thresholds may also be reviewed. There are several types of data cleaning that depend on the type of data such as phone numbers, email addresses, employers etc. IEEE Projects on Data AnalyticsQuantitative data methods for outlier detection can be used to get rid of likely incorrectly entered data. Textual data spell checkers can be used to lessen the amount of mistyped words, but it is harder to tell if the words themselves are correct