About Ravi Satyadarshi

Passionate developer & designer. Working in Microsoft .NET & SQL platform and developed many window & web applications. Working in several R&D teams, contributing and influencing design and development at every stage of the product life-cycle. I possess an excellent understanding of programming within the Microsoft .NET environment and Microsoft SQL Server. The key of the success is creating good relationships in the work environment and continually improving my skills and knowledge. I am focused on broadening my cultural horizons in order to provide more efficient solutions. I strongly love programming in C#.NET , ASP.NET as front end , and SQL Server in back end along with jQuery,Java Script for scripting purpose. For any suggestion or query you can contact me on satyadarshi.ravi@gmail.com.

Encrypt Password in SQL

Hello folks,

Today we will see how we can encrypt password before saving into database table.

There are many ways to implement this feature like defining Asymmetric keys and using that into table/sp or use some hash algo to encrypt password etc but we will add some complexity into encryption stuff.

Objective:  Our goal is to generate very complex and encrypted password which can’t be hacked (not even by database guys using sql injection etc).


Step 1: Create a table that will hold username, password and other details. See below sample. Continue reading


Data Mining Methodology

Data Mining:CRISP - Data mining

Data mining can be defined as the process of extracting valid, authentic, and actionable information from large databases using various data mining techniques like machine learning, artificial intelligence (AI) and statistics to derive patterns and trends that exist in data. These patterns and trends can be collected together and defined as a mining model.

Almost all industries these days are taking advantage of this technique including manufacturing, marketing, chemical, aerospace etc. to increase their business efficiency. Therefore the needs of a standard data mining process increased dramatically which should be easy, comprehensive, reliable and uniform across the industry.

Data Mining Methodology:-

As a result in 1990 a Cross Industry Standard Process for Data Mining (CRISP-DM) first published the uniform and standard process for data mining by defining below 7 steps

1. Defining the problem – Understanding Business Process Continue reading

Data Mining Architecture

Data Mining: 

Data mining is described as the process of discovering or extracting interesting and meaningful knowledge from large volume of data which are stored in multiple data sources like databases, file system , data warehouse etc. The knowledge extracted from data mining contributes a lots of benefit to business strategies, scientific & medical research, governments and individual. Data warehouse systems has been designed to provide analytical reports that helps (DSS- Decision Support System) business users to make decisions.

Data Mining Architecture Continue reading

Data Mining Techniques

In my last article an overview of data mining has been provided. In this article we will see the different techniques or algorithm we use in data mining process.


We all know that necessity is the mother of invention. Need of people changes with the time and to feed our hunger and need, lots of technology are also evolving around the world. Also we can do same work in no of ways and it all depends on the requirement, available time frame and our budget. Lots of data mining techniques and algorithms are available in market from variety of technology vendors in market. Described below are most common data mining techniques-

1. Association:

  • This is one of the best known data mining technique available in market these days.
  • Using this technique a pattern is discovered based on the relationship between items in same transaction of group.
  • This technique is also known as relation technique because of above reason.
  • We use association in Market Basket Analysis to identify a set of products a customer purchase frequently together.
  • Retailer are using this technique to research customer’s buying habits.
  • Based on historical sales data retailers might find out that customers always buys snakes/chips when they buys beers therefore they can put beer and chips/snakes together to save customer time and increase their sales.
  • Another example can be the recommended/suggested videos of similar nature when you browse youtube videos. Or when you visit any e-commerce website they website recommend you few more products which people buys together mostly like cellphone cover and external memory card while browsing cell phone etc.

Continue reading