The demand for “all around” testers is growing.

What does the phrase “all around” mean? It means that testers should be equipped with the ability to test the system’s functionality through traditional “point, click, and verify” testing methods AND be able to utilize their technical expertise to verify all aspects of a system. That technical expertise includes operating system, interface, and database verification skills. In this blog, I will highlight the importance of good Structured Query Language (SQL) skills.

How important are SQL skills for a Software Tester?
As a Software Quality Assurance Tester, I have worked on several different applications. Some of the applications require strong SQL verification skills, some of them required medium skills, and for some of the applications, I didn’t need any SQL knowledge.

Even if you are working on front-end testing of different web applications to verify the site functionality, you may require basic SQL skills. SQL skills is required to verify test data: insert, update, and delete the test data values in the database. You will need to use SQL queries against the SQL server database for this particular test approach.

If you are strictly working on back-end testing projects (i.e. Data Warehousing, ETL processing or File-based data load, Interface testing etc.), SQL Query knowledge is a must have skill. As part of this testing, you will need to compare data before and after processing. You may be writing complex queries with select statements and in order to do that you will need to the relation between the tables, columns, and the query before you can write any kind of SQL statements. You will also need to understand how to write the different types of SQL Statements to verify the test data.

SQL skills is also useful if you are working on Business Intelligence (BI) reporting projects. This is where you will require advanced SQL knowledge and need to learn how to write complex SQL queries using Aggregates, Group By and Having along with complex Joins. As part of reports testing, you may need to verify complex calculations and analyze data along with understanding complex data structures in relational or data warehousing (star or snowflake schema).

From my past experiences, I believe a tester should have the below database and SQL knowledge:

 

• • Recognize the different types of databases (i.e. SQL Server vs Oracle and Relational database vs Star/Snoflak schemas)

• • Connect to the database using different SQL connection clients

• • Understand the relationship between database tables, keys, and indices

• • Write basic select queries or SQL statement along with more complex join queries

• • Interpret more complex queries

SQL statements we frequently use in testing are:

• • Data Manipulation Language (DML): Used to retrieve, store, modify, delete, insert, and update data in the database. Examples: SELECT, UPDATE and INSERT statements.

• • Data Definition Language (DDL): Used to create and modify the structure of database objects
  • in the database. Examples: CREATE, ALTER and DROP statements.

• • Transactional Control Language (TCL): Manages different transactions occurring within the database. Examples: COMMIT, ROLLBACK statements.

• • Inner Join: Retrieves the matched records from both tables.

• • Distinct: Retrieves the different values from one or more fields.

• • In: This operator is used to find the value is within the list or not.

• • Between: This operator is used to retrieve the values with in a range.

• • Like: This operator is used perform pattern matching using wildcards; it is used in the where clause.

• • Order By Clause: Sorts the table records in ascending or descending order. Default order is ascending.

• • Group By: Use Group By statements with the aggregate function to group the result set with one or more columns.

• • Aggregate Functions: Performs a calculation on a set of values and return a single value. Example: Avg, Min, Max, Sum, count etc.

Throughout my 20+ years of IT experience with SQL I’ve seen the benefits and usefulness of SQL Skills applied in the testing projects. I would suggest testers acquire some knowledge of SQL to become the “all around,” versatile tester that clients need and value.

Please reach out if you have any questions on SQL or like to learn SQL. You can also check out our SQL/Database/SSRS Bootcamp here so that you can acquire valuable SQL/Database skills over 3 weekends.

Robotic process automation (RPA) is an emerging form of clerical process automation technology based on the notion of software robots or artificial intelligence (AI) workers.

Defining RPA: Taking the robot out of the human
At first glance, RPA may sound like theoretical tech along the lines of self-aware artificial intelligence, but the actual mechanics are much more mundane and connected to modern business operations.

RPA involves the use of automated “bots” to manage a wide variety of internal processes that would otherwise require manual operation. These tasks can include anything from processing insurance claims to opening new bank accounts, but RPA solutions are often used for time-consuming and arduous jobs that don’t take advantage of knowledge workers’ specialized expertise and skill sets. As TechTarget explained, record management, handling transactions and running database queries are all viable candidates for RPA implementation.

When used in the right environments, RPA tools can replace thousands of manhours handling repetitive tasks, freeing up staff members to tackle more value-driven projects.

What are RPA robots?
When we talk about robots as they pertain to RPA, what we really mean is software. Bots in this sense refer to programs that simulate a human activity, like crawling data repositories for information, for instance. By automating bots to respond to particular events with a predefined set of actions, businesses can dramatically increase the speed of their internal workflows, while also minimizing the potential for costly mistakes like data entry errors.

The important criteria to keep in mind when discussing RPA and its potential applications is structure and repeatability. RPA bots are not “intelligent” or “thinking” the same way machine learning and AI tools are. At their most fundamental capabilities, RPA solutions are not able to self-improve or think critically about the task at hand. They just do what they’re told.

In this way, RPA is a very different form of technology than ML or AI. It is arguably more beneficial and relevant to modern-day business, especially among organizations that rely on numerous repetitive workflows to operate. While RPA isn’t a self-learning asset, it can be configured to spot errors and mistakes in internal processes and flag them accordingly. With the combined benefits of accelerated business speed, increased workflow accuracy and employee productivity, it’s easy to see why this technology has generated a lot of interest.

Major RPA software tools
When vetting potential RPA platforms, decision-makers should look for solutions that can be applied to workflows specific to their industry. RPA software may not necessarily be custom designed with a certain vertical in mind, but it should be able to support common processes and the most beneficial applications.

With that in mind, there are three RPA software leaders that can support most automation use cases. They are:

• UiPath
• Automation Anywhere
• Blue Prism

All are powerful tools that simplify the creation and deployment of RPA bots. Choosing between them will come down to several factors, including your projected course along the RPA maturity curve and the specific nature of your implementation. You can learn more about the different RPA platforms in our vendor comparison white paper, available here.

Industry-specific RPA applications are listed below.

• Insurance: RPA can streamline time-intensive tasks like claims processing that are both relatively simple to conduct and repeatable.
• Human resources: Many HR tasks are ripe for RPA implementation. Employee onboarding, for example, includes a number of processes that could easily be handled by automated bots.
  Health care: There are a wide variety of internal tasks that can be enhanced through RPA, including processing medical insurance claims, managing patient records while complying with industry regulations and executing billing jobs.
• Financial services: Banks and other financial institutions can automate account openings, financial transactions and comply with audit requests.
  Customer service: Contact center operations can be drastically improved by using RPA to integrate information from various databases and place it in the hands of customer service representatives.
• Payment processing: The processing of clearinghouse payments is sufficiently routine that it can be automated. A Fortune 100 diversified bank recently used RPA to automate its ACH (automated clearing house) payment processing.
• Request processing: RPA can be used to automate certain routine customer requests. A leading European food producer used RPA to automate the processing of simple customer order inquiries, reducing manual effort by 40-60%.
• Validation: RPA is also useful in performing tasks involving validation, as it is easy for computers to tell if one thing is not exactly the same as another. As an example, BNY Mellon automated web-based client record reconciliation, freeing its employees from a tedious, mistake-prone process.

Robotic process automation (RPA) is an emerging form of clerical process automation technology based on the notion of software robots or artificial intelligence (AI) workers.

Defining RPA: Taking the robot out of the human
At first glance, RPA may sound like theoretical tech along the lines of self-aware artificial intelligence, but the actual mechanics are much more mundane and connected to modern business operations.

RPA involves the use of automated “bots” to manage a wide variety of internal processes that would otherwise require manual operation. These tasks can include anything from processing insurance claims to opening new bank accounts, but RPA solutions are often used for time-consuming and arduous jobs that don’t take advantage of knowledge workers’ specialized expertise and skill sets. As TechTarget explained, record management, handling transactions and running database queries are all viable candidates for RPA implementation.

When used in the right environments, RPA tools can replace thousands of manhours handling repetitive tasks, freeing up staff members to tackle more value-driven projects.

What are RPA robots?
When we talk about robots as they pertain to RPA, what we really mean is software. Bots in this sense refer to programs that simulate a human activity, like crawling data repositories for information, for instance. By automating bots to respond to particular events with a predefined set of actions, businesses can dramatically increase the speed of their internal workflows, while also minimizing the potential for costly mistakes like data entry errors.

The important criteria to keep in mind when discussing RPA and its potential applications is structure and repeatability. RPA bots are not “intelligent” or “thinking” the same way machine learning and AI tools are. At their most fundamental capabilities, RPA solutions are not able to self-improve or think critically about the task at hand. They just do what they’re told.

In this way, RPA is a very different form of technology than ML or AI. It is arguably more beneficial and relevant to modern-day business, especially among organizations that rely on numerous repetitive workflows to operate. While RPA isn’t a self-learning asset, it can be configured to spot errors and mistakes in internal processes and flag them accordingly. With the combined benefits of accelerated business speed, increased workflow accuracy and employee productivity, it’s easy to see why this technology has generated a lot of interest.

Major RPA software applications
When vetting potential RPA platforms, decision-makers should look for solutions that can be applied to workflows specific to their industry. RPA software may not necessarily be custom designed with a certain vertical in mind, but it should be able to support common processes and the most beneficial applications.

With that in mind, there are three RPA software leaders that can support most automation use cases. They are:

• UiPath
  Automation Anywhere
  Blue Prism

All are powerful tools that simplify the creation and deployment of RPA bots. Choosing between them will come down to several factors, including your projected course along the RPA maturity curve and the specific nature of your implementation. You can learn more about the different RPA platforms in our vendor comparison white paper, available here.

Industry-specific RPA applications are listed below.

• Insurance: RPA can streamline time-intensive tasks like claims processing that are both relatively simple to conduct and repeatable.
• Human resources: Many HR tasks are ripe for RPA implementation. Employee onboarding, for example, includes a number of processes that could easily be handled by automated bots.
  Health care: There are a wide variety of internal tasks that can be enhanced through RPA, including processing medical insurance claims, managing patient records while complying with industry regulations and executing billing jobs.
• Financial services: Banks and other financial institutions can automate account openings, financial transactions and comply with audit requests.
  Customer service: Contact center operations can be drastically improved by using RPA to integrate information from various databases and place it in the hands of customer service representatives.
• Payment processing: The processing of clearinghouse payments is sufficiently routine that it can be automated. A Fortune 100 diversified bank recently used RPA to automate its ACH (automated clearing house) payment processing.
• Request processing: RPA can be used to automate certain routine customer requests. A leading European food producer used RPA to automate the processing of simple customer order inquiries, reducing manual effort by 40-60%.
• Validation: RPA is also useful in performing tasks involving validation, as it is easy for computers to tell if one thing is not exactly the same as another. As an example, BNY Mellon automated web-based client record reconciliation, freeing its employees from a tedious, mistake-prone process.

Testing is a process, where we verify and validate that the actual matches the expected. That’s one of the easiest way to put this complex process into wording. And automation basically means something which allows replacing man with a machine. The most basic example of automation is a “wheel”. Test Automation is a process where we automate the process of testing. Or in other words – Software test automation refers to the activities and efforts that intend to automate engineering tasks and operations in a software test process using well-defined strategies and systematic solutions.

The following objectives are expected to be achieved from the Test automation –

• Decrease in cost
• Decrease in time to delivery
• Effective utilization of resources
• Improved quality
• Requirements of Test Automation can be depicted in the following diagram

A lot of both commercial and open source solutions are available in the market out there. Commercial solution comes with hefty license fees, where as open source solutions are freely available. And there are a lot of differences amongst these solutions.

Example of commercial solutions are – UFT from HP, RFT from Microsoft, Smart Bear from Test complete etc.
Examples of open source solutions are – Watir, Selenium, Sahi etc.

Out of the available open source solutions in the market, Selenium is the most popular choice. The reason for its popularity is the cool feature set this tool has. But before that, let us talk about the history of Selenium. Selenium was created in 2004 by Jason R Huggins. Some of the cool features of selenium are –

• It supports multiple browsers like Internet explorer, Mozilla Firefox, Chrome.
• It supports scripting in multiple languages like C#, Java, Perl, Python etc
• It supports multiple operating systems like the tests of Selenium can run on windows, linux, mac…

Selenium is released under Apache 2.0 license which means we can download and use it at no cost. The home page of Selenium is – http://www.seleniumhq.org/. Selenium is not one single test automation tool. But it is a project which has four major components –

• Selenium IDE
• Selenium RC
• Selenium Webdriver
• Selenium Grid

Selenium IDE

Selenium IDE is a Firefox plugin. It is used for recording and playback of scenarios. It allows us to save our tests in Java, Ruby and other programming languages. Selenium IDE doesn’t support by default usage of programming constructs and also doesn’t have support for reports.

Selenium RC

Selenium RC, also known as Selenium remote control, also known as Selenium 1.0 is one of the oldest component of Selenium which is no longer used now. Selenium RC works by injecting a java script proxy server in the browser and sends command to it, which then automates the browser and sends the response back.

Selenium Webdriver

Selenium Webdriver is also known as Selenium 2.0. It works on the concept that browser own API can be extended to automate the browser. So each browser has its own webdriver which allows to automate the browser. The selenium most common implementation is of webdriver.

Selenium Grid

Selenium Grid, uses selenium rc in two modes hub and node. It allows the tests to run in parallel on different systems using same or different browsers. This allows to save time, the maximum time taken is the time taken by the longest test to run. It is also used for Cross browser testing.