Timothy Smith
Three example alternatives of tracking behavior by data masking the specific time

Data Masking or Altering Behavioral Information

June 26, 2020 by

As tracking behavioral data becomes increasingly popular, firms may overlook areas where they can collect the same information while data masking details that can be used in a compromise. Behavioral data collection can be extremely dangerous as it allows attackers a wide range of attacks, from spoofing targets to automating custom attacks on targets. Since behavior can reveal key details about us, this information may be as costly as private identifiable information. When tracking behavioral data, we want to weigh risks, and, in some cases, we can accomplish the same result without specific details. In other cases, we may want to mask specific behavioral information on reports that are generated, even if we retain the specific time. We’ll look at a method where we can accomplish either – updating data to remove time or data masking specific time while returning the information we want.

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Aveek Das
Function URL up and running

Getting started with Azure Function Apps

June 25, 2020 by

In this article, I am going to explain how to get started with Azure Function Apps. In my previous article, An introduction to Serverless Applications, I have mentioned the serverless architecture and the various cloud offerings to develop serverless applications. As we know, in serverless architecture, the users only write the business logic code, and all other worries are taken care of by the cloud provider. This helps businesses to quickly implement solutions and ship it to customers with more quality. Also, another important point about serverless applications is that they are scalable on-demand, which means as a developer, we no longer need to monitor or manually pull up the resources when the executions are more.

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Aveek Das
AWS Lambda – Serverless Applications

An introduction to Serverless Applications

June 25, 2020 by

In this article, I am going to describe what are serverless applications and how are these developed. I will also introduce the concepts of serverless computing and how to deploy one using Azure Functions. This article is targeted towards most of the data professionals who want to gain some basic knowledge of serverless applications and the underlying architecture and cloud computing. In recent times, cloud computing has become one of the most important domains for many big organizations and it has thus become essential for all to have some basic information on the same.

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Dinesh Asanka
Final package after inclusion of Conditional Split.

Using the SSIS Script Component as a Data Source

June 25, 2020 by

Introduction

SSIS Script component is one data transformation tasks in SQL Server Integration Services (SSIS). SSIS is an integration tool in the Microsoft BI family to extract data from heterogeneous data sources and transform it to your need. Apart from the standard data sources such as databases, text files, excel files, and web services, there can be instances where you need to retrieve non-traditional data sources. For example, let us say you want to extract the details of text files such as file sizes, created date, etc. In these types of scenarios, traditional data sources cannot be used.

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Jignesh Raiyani
Inserted and Deleted magic tables in SQL Server

Magic Tables in SQL Server

June 23, 2020 by

There are Magic Tables (virtual tables) in SQL Server that hold the temporal information of recently inserted and recently deleted data in the virtual table. INSERTED and DELETED are two types of magic tables in SQL Server. An INSERTED magic table is populated with INSERT and UPDATE operations and DELETED magic table is populated with UPDATE and DELETE operations.

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Jignesh Raiyani
Calling SQL Server Procedure inside the Function

Execute a SQL Server procedure inside a function

June 23, 2020 by

In this article, we will ensure that the execution of the SQL Server procedure inside the function is possible. A common understanding of the database developer is that the procedure cannot be utilized or executed inside a user-defined function because the user-defined function does not allow performing DML operation with the table. The procedure is allowed to play with the database and its property, whether a user-defined function isn’t. That should be the essential reason behind allowing the execution of a SQL Server procedure inside the function.

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Timothy Smith

Security Testing with extreme data volume ranges

June 19, 2020 by

When we develop security testing within inconsistent data volume situations, we should consider our use of anti-malware applications that use behavioral analysis. Many of these applications are designed to catch and flag unusual behavior. This may help prevent attacks, but it may also cause ETL flows to be disrupted, potentially disrupting our customers or clients. While we may have a consistent flow of data throughout a time period – allowing for a normal window of behavior to occur – we may also have an inconsistent data schedule or inconsistent amount of data that cause these applications to flag files, directories, or the process itself.

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Aveek Das
Sample Analysis - Sales Pipeline

Getting started with Amazon QuickSight

June 18, 2020 by

In this article, I am going to introduce Amazon QuickSight and how to visualize data using it. Amazon QuickSight is a data visualization tool offered by Amazon hosted on AWS and is available across multiple locations. As per the statement provided on the official website it says: “Amazon QuickSight is a fast, cloud-powered business intelligence service that makes it easy to deliver insights to everyone in your organization.” Using QuickSight, users can create different analyses and then integrate those in a dashboard and share them with people within the organization.

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Dinesh Asanka
Experiement configuration is Azure ML Studio.

Introduction to Azure Machine Learning using Azure ML Studio

June 18, 2020 by

Introduction

Let us see how Azure ML studio can be used to create machine learning models and how to consume them in this series. As we discussed during the data mining series, we identified the challenges in the predictions in data. In the Azure Machine learning platform, machine learning workflows can be defined in easy scale models in the cloud environment. Today will be looking at how datasets can be uploaded.

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