Now a days people live to work fast and easily. They do not like to west time. When we think about tradition exam technic in that teacher have to write paper and they have to print that paper for all of the class students. Students want to write that in…

Power BI is a cloud-based analysis service that provides rapid insight and is used to extract and visualise data. Power BI brings together data from multiple sources to give you a comprehensive view of your company’s information assets.

This means that with Power BI you can see all your data…

A Power BI dashboard is a single page, often called a canvas, that tells a story through visualizations. Because it’s limited to one page, a well-designed dashboard contains only the highlights of that story. Readers can view related reports for the details. Dashboards are a feature of the Power BI service only.

Import Data from available different sources

Preview of selected data

Introduction of PowerBI:

Power BI is a collection of software services, apps, and connectors that work together to turn your unrelated sources of data into coherent, visually immersive, and interactive insights. Your data may be an Excel spreadsheet, or a collection of cloud-based and on-premises hybrid data warehouses. …

Let’s start with Neo4j

Neo4j is a graph database management system developed by Neo4j, Inc. Described by its developers as an ACID-compliant transactional database with native graph storage and processing,Neo4j is available in a GPL3-licensed open-source “community edition”, with online backup and high availability extensions licensed under a closed-source commercial license.Neo also licenses Neo4j with these extensions under closed-source commercial terms.

So first download neo4j in your desktop and active DBMS and open neo4j browser.

Relationship type ACTED_IN

Using Orange I learned about discretization, continuization, Normalization, Randomization


Discretization replaces continuous features with the corresponding categorical features:

import Orange
iris ="")
disc = Orange.preprocess.Discretize()
disc.method = Orange.preprocess.discretize.EqualFreq(n=4)
d_iris = disc(iris)
print("Original dataset:")
for e in iris[:4]:
print("Discretized dataset:")
for e in d_iris[:4]:


Given a data table…

Pooja Lo

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