TOP 5 ADVANCED TECHNIQUES OF DATA ANALYSIS

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Welcome To Loginworks Software
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TOP 5 ADVANCED TECHNIQUES OF
DATA ANALYSIS
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WHAT IS DATA ANALYSIS?
WHY DATA ANALYSIS? We live in a digital era where
data converts in a Nanosecond that is much faster
than a normal human capability. In the corporate
sector, employees work on a large volume of data
which is extracted from different sources like
Social Network, Media, Newspaper, Book, cloud
media storage etc. But sometimes it may create
some difficulties for you to summarize the data.
Sometimes when you fetch the data from other
sources, you cannot predict that how much data
will be stored in the database. As a result, the
data set becomes more difficult and takes enough
time for analyzing the process. So, lets explain
the solution to this problem. Try to fetch data
sets in the form of a new category and retrieve
the data type whatever data type you want for
data filtration. Data Analysis technique provides
the good amount of data quality. Excel is the
best tool for data Analysis process. Data
Analysis is much useful in Corporate Analysis,
Data management, Market Analysis, Risk
Management, and Fraud Detection.
Data Analysis is the new emerging way of find out
statistical patterns and relevant information by
using data analysis. Data Analysis contains a set
of processes like Data Modelling, Data
Integration process, Data processing, and Data
Evaluation etc. By using data Analysis, you can
easily divide a big number of data sets into
small piece statistical patterns, later you can
feed them in the database easily.
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BENEFITS OF DATA ANALYSIS

• Data Analysis attributes can easily find the
  missing patterns from the inconsistent data that
  increases the optimization speed of the optimal
  result.
• If you work in a consistent way until the
  deployment of the business objectives that
  increase the brand loyalty that will really help
  you in marketing campaigns. The benefit is that
  customers can directly communicate with the
  organization to serve better.
• By the completion of project delivery to the
  stakeholders/customers, that surely increases the
  trust in your organization and the work that you
  delivered. It simply can increase your customer
  base.
• Data Analysis techniques and tools help in making
  the big decision to increase an organizations
  revenue.
• By using data Analysis, it can convert complex
  and inconsistent data into a general structure
  that customer can understand easily.

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TOP 5 TECHNIQUES OF DATA ANALYSIS
CLASSIFICATION ANALYSIS Classification
analysis is used to find relevant and important
information of the metadata and data sets. This
analysis is used to retrieve the different type
of data in different class objects.
Classification is just like as clustering that
segments data format into different segments
called object classes. Unlike classification,
data analysts contain data for different cluster
or classes. So, you need to apply classification
algorithms analysis to find out that how newly
stored data should be verified. For an example,
an Outlook email is the best example of
classification algorithm analysis. In Outlook,
algorithms are used to characterize the format of
an email as spam or legitimate. Classification
algorithm contains its properties as follows
1. Classification Analysis 2. Excel Analysis
V-H Lookup 3. Pivot Table 4. SQL Analysis 5.
Regression Analysis
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Classification Analysics Code
CLASSIFICATION ANALYSIS METHODS FOR ANALYZING THE
DATA. Logistic Regression Classification This
type of analysis technique provides machine
learning analysis algorithm for data
classification. In this classification, the
probability describes the possible result of data
modeling by using a logistic method function.
Logistic regression is highly designed for only
classification purpose and is used to understand
the influence of independent variables at a
single outcome of the dependent variable. But it
will be used only when the predictive variable is
binary that means all variable are independent of
each other.
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Naïve Bayes This kind of classification
algorithm is totally based on Bayes theorem that
works with the prediction in each pair of
independence features. Naive Bayes theorem works
well in several real-life situations like as spam
filtering and document classification. This
algorithm contains training data to evaluate the
required parameters. But Naive Bayes is well
known for its bad estimator formula.
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Google Analytics Function
EXCEL ANALYSIS
LOOKUP FUNCTIONS
Excel is the most powerful feature of data
analytics that is used to determine the data in
terms of Insertion of the data, data computation,
modification of the data, and deletion of the
data. It is a most sophisticated data analysis
tool. Excel provides a way to solve big data in a
wide variety of formats like VBA, Macro,
Function, and Pivot filters. I would prefer to
learn first excel if you are trying to go for R
and Python programming languages. So, I will tell
you about the whole concept of data analysis
technique of excel. There are many data analysis
techniques as follows.
These functions retrieve data from the excel
database in a quick manner. These are very
powerful functions and widely used on a daily
basis work in the corporate world. Lookup
functions are also can be used within sheets and
with multiple sheets at the same time. For this
reason, you will have to provide a data range for
data result. V-lookup and H-lookup both are types
of lookup functions. So, lets understand how it
works for data analysis.
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V-LOOKUP FUNCTION This lookup function works
vertically in the sheet and it helps to find out
the corresponding record in a table. So, lets
understand this lookup function as follows. First
of all, create a table in excel. I have already
created a table below. There are 8 columns like
as Name, Policy Amount, Joining Date, DOB,
PINCODE, RAILWAY CODE, AGE, and ADDRESS. By
default, Excel takes text number values.
Although, it does not change automatically as it
is case sensitive formula. If ever you define a
date format you will have to convert its text to
date by right clicking on Format Cells. In the
column Joining date and DOB will be shown in
their real format.

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Now, I want to retrieve all details of John
from the table. Here, is the result as
follows. OUTPUT
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V-lookup
Now, understand how it happened. I have just
created a formula of V-lookup and syntax like as
Vlookup (lookup_value, table_array,
Col_index_num, range_lookup). First of all, it
selects a lookup value that means the target
value that you need. Second, define table range
including column names. Third, provide the index
number of selected column name that is required
for. Fourth, range lookup that means either False
or True. You can also put 0 or 1 for range lookup
because 0 indicates False and 1 indicates True
but if you choose False that will give you an
exact result and if you go with True that gives
the appropriate result but not exact as
False. So, I recommend that if you want to find
the exact result of a particular search value
then select False. In the above result, once you
apply the formula you will get an only single
result. For this reason, if you need all the
details just drag the bottom right corner of a
selected cell to the right side of the
sheet. Note Lookup functions always work from
left to right but not right to left and it takes
search value from the rows.
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PIVOT TABLE
A pivot table is a key program feature that
allows data to summarize reorganize selected
multiple rows and columns in a database table or
spreadsheet to get the desired report. It a
mainframe of excel database. Hence, a pivot table
can solve a big amount of data set in one excel
sheet. So, lets just understand with a real
example. For this reason, I have taken the bulk
data as follows.
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pivot table is a key program
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Now, I want to fetch the total amount from the
table where the country name should be India
and Model Name should be Apple. So, lets
figure this with applying pivot table. First of
all, select the complete table and open the
insert row from the toolbar. Then, select pivot
table and you will see two options (New Workbook
and Existing Workbook). If you choose new
workbook then pivot table framework will show in
the new spreadsheet but if you go with existing
workbook then it will show on the same sheet
where you created the table
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DATA ANALYSIS THROUGH SQL
SQL is known for Standard Query Language.
Although, SQL is not a language but a framework
or tool that is used to solve millions of data in
a quick manner by using its features. SQL is
totally depending on tables and its functions. It
provides data addition, insertion, and deletion
etc. It contains four commands like as DML (Data
Manipulation Language), DDL (Data Definition
Language), DCL (Data Control Language), and TCL
(Transaction Control Language). Now, lets do
some practical analysis using SQL. So, lets
assume a table Student as follows.
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Now I want to fetch details of ID1 from the
table Student.
Result
Result
Result
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REGRESSION ANALYSIS
This type of analysis is used to define
predictive modeling that further evaluates the
relationship between an independent variable that
defines as a predictor and dependent result. This
technique is mainly used for time series data
modeling, forecasting, and finding the effect of
the data variables. Understand with an example, a
relationship between the road accidents and fast
rash driving is the best example through
regression. Regression analysis is a very useful
tool for analyzing data and data modeling.
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Regression analysis
Regression analysis works independently by using
mathematical equations. So, lets understand with
an example. Global warming contains the reducing
average of snowfall and predicts how much
snowfall you think will fall in this month. Now,
look at the existing table that you could guess
around 11-20 inches. Thats a nice thought, but
you could guess better than this with the help of
the regression chart.
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CONCLUSION In the end, we have learned the top
techniques of data analysis. If you want to serve
better for your corporate world then choose these
analysis techniques. There are more data analysis
tools and techniques available in the market but
I only explained these 5 techniques of data
analysis. Because these techniques are being used
in todays corporate world. I hope you enjoyed my
article.
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