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Data Analysis & Automation : An Overview

EasyChair Preprint no. 6080

23 pagesDate: July 14, 2021


Automation has helped humanity grow and achieve many things. Data Analysis and Handling along with Data Visualization is an integral part in the Industry. This is the core ideology behind this review paper. The reduced the manual work required in making the daily Dashboard Report by using the knowledge of IT Automation, specifically data handling and analysis process, is a vastly used method in all sectors.

The initial process was to work on the front end to develop the required visuals and make them user friendly while making progress in the back end development which is the core aspect when comes to the Automation aspect of any dashboard development project. This paves way to give us an overview about what the actual dashboard automation steps look like and thus giving readers a comprehensive idea about Dashboard Development for any industry.

The software stack used to in this review paper are majorly related to data handling and visualization. Tools like MS SQL Server Management Studio and MS Power BI are a perfect amalgamation required to create professional looking dashboard with cutting edge back end to drive the automation. The paper elegantly gives the overview about SSIS packages and how to connect them to Power BI via an SQL data source connection for regular data refresh, thus reducing the manual work required and simultaneously helping the clients access a fully automated and interactive dashboard for their daily needs.

The paper aims to build a growing community by helping the readers to develop an insight focusing more on development of efficient, effective and elegant looking dashboards for data intensive sectors like Multinationl Company where an aesthetically pleasing and efficient dashboard is a necessity to give meaningful insight about highly complex data to anyone without the effort needed to explain them about the complexities within.

Keyphrases: SQL, SSIS, SSMS

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Archit Srivastava and Veena K Divya and Arvind Bhagwath},
  title = {Data Analysis & Automation : An Overview},
  howpublished = {EasyChair Preprint no. 6080},

  year = {EasyChair, 2021}}
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