Dinesh Asanka

Dinesh Asanka
Recommender System in Azure Machine Learning.

Designing Recommender Systems in Azure Machine Learning

April 13, 2021 by

In this article, we will be discussing how to design a Recommender System in Azure Machine learning which is the next article in the Azure Machine Learning series. During this lengthy article series on Azure Machine Learning, we have discussed multiple machine learning techniques such as Regression analysis, Classification Analysis, Clustering and Anomaly detection of Time Series. Further, we have discussed the basic cleaning techniques, feature selection techniques and Principal component analysis, Comparing Models and Cross-Validation and Hyper Tune parameters in this article series to date.

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Select Tables and Views to create the OLAP Cube.

Multi-language support for SSAS

April 8, 2021 by

Introduction

After discussing many features in SQL Server Analysis Services (SSAS) in order to carry out much richer analytics activities, we are going to discuss another feature in SSAS named Multi-language support for SSAS. In a previous article, we discussed how to create SSAS OLAP Cubes and how to access the OLAP cube using Excel. Further, we discussed how to include hierarchies in SSAS in order to improve the data analysis capabilities. In addition to those features, we discussed how to create perspectives in OLAP Cubes and how to perform management activities in SSAS.

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Filtering the anomalies in the time series.

Time Series Anomaly Detection in Azure Machine Learning

April 1, 2021 by

In this article, we will be discussing how to use Time Series Anomaly Detection in Azure Machine Learning and this article comes next in the Azure Machine Learning series. During this article series on Azure Machine Learning, we have discussed multiple machine learning techniques such as Regression analysis, Classification Analysis and Clustering. Further, we have discussed the basic cleaning techniques, feature selection techniques and Principal component analysis, Comparing Models and Cross-Validation and Hyper Tune parameters until today in this article series.

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Implementing Tune Model Hyperparameters in Azure Machine Learning

Tune Model Hyperparameters for Azure Machine Learning models

March 25, 2021 by

Introduction

In this article, we will be discussing how to Tune Model Hyperparameters to choose the best parameters for Azure Machine Learning models. During this article series on Azure Machine Learning, we have discussed multiple machine learning techniques such as Regression analysis, Classification Analysis and Clustering. Further, we have discussed the basic cleaning techniques, feature selection techniques and Principal component analysis, Comparing Models and Cross-Validation until today in this article series.

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Elastic Jobs in Azure SQL Database

February 18, 2021 by

Introduction

I have dedicated this article to the topic of Elastic Jobs in Azure SQL Database which is in Public Review. This feature allows you to run scheduled tasks in your Azure SQL Databases. This is similar to SQL Server Agent you have in the On-prem SQL Server versions. However, in Elastic Jobs, you can execute the scheduled tasks in multiple Azure SQL Servers and multiple Databases which is an added advantage when considering the features of SQL Server Agent. Further, this execution performs parallelly.

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Default Data Masking Option Azure SQL.

Dynamic Data Masking in SQL Server

February 2, 2021 by

Introduction

In this article, we will be looking at how to perform and access Dynamic Data Masking in SQL Server. Data Masking is the process of hiding data with different rules. One of the main reasons to apply data masking is to protect Personal Identifiable Information (PII) and sensitive data from unauthorized access. Even when unauthorized users access these data, they will not be able to view the actual values. This article will look at the possibilities of applying Dynamic Data Masking in SQL Server and we will look at how Dynamic Data masking can be applied to the Azure SQL Databases as well.

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Usage of Classification with Clustering technique.

Clustering in Azure Machine Learning

January 13, 2021 by

Introduction

In this article, we will be discussing Clustering in Azure Machine Learning which is another machine learning technique such as Regression analysis, Classification analysis. During this article series, we have discussed the basic cleaning techniques, feature selection techniques and Principal component analysis, Comparing Models and Cross-Validation until today. We will introduce further few techniques that were not discussed before in this article as well. Previously, we have discussed how to perform clustering in SQL Server during the SQL Server Data Mining series.

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Comparing models with the inclusion of Cross Validation in AML.

Cross Validation in Azure Machine Learning

January 4, 2021 by

Introduction

After discussing a few algorithms and techniques and comparison of models with Azure Machine learning, let us discuss a validation technique, which is Cross-Validation in Azure Machine Learning in this article. During this series of articles, we have learned the basic cleaning techniques, feature selection techniques and Principal component analysis etc. After discussing Regression analysis, Classification analysis and comparing models, let us focus now on performing Cross-Validation in Azure Machine Learning in order to evaluate models.

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Multiclass classificaiton for comparison in Azure Machine Learning.

Comparing models in Azure Machine Learning

November 23, 2020 by

Introduction

After discussing a few algorithms and techniques with Azure Machine Learning let us discuss techniques of comparison in Azure Machine Learning in this article. During this series of articles, we have discussed the basic cleaning techniques, feature selection techniques and Principal component analysis, etc. After discussing Regression and Classification analysis let us focus more on performing comparison in Azure Machine Learning.

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The Sample experiment for the Classification technique.

Prediction with Classification in Azure Machine Learning

October 30, 2020 by

Introduction

After discussing Regression in the previous article, let us discuss the techniques for Classification in Azure Machine learning in this article. Like regression, classification is also the common prediction technique that is being used in many organizations. Before the regression we have discussed basic cleaning techniques, feature selection techniques and Principal component analysis in previous articles, now we will be looking at data classification techniques in azure machine learning in this article.

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Exporting SSRS Reports to Multiple Sheets in Excel with dynamic sheets.

Exporting SSRS reports to multiple worksheets in Excel

September 11, 2020 by

Introduction

SQL Server Reporting Services (SSRS) has multiple options of exporting data into a variety of formats and we will be discussing the options of exporting SSRS Reports to multiple sheets of excel. In SSRS, there are multiple formats available to export reports depending on the user’s needs. Microsoft Word, Microsoft Excel, Microsoft PowerPoint, Tiff file, MHTML (Web Archive), CSV (comma delimited) and XML file with report data are the popular formats that can be exported from SSRS as shown in the below screenshot.

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Creating a Weekly schedule for the Standard Subscription in SSRS.

Enhancing Customer Experiences with Subscriptions in SSRS

August 28, 2020 by

Introduction

We are going to discuss a very important option in SQL Server Reporting Services (SSRS), which is Subscriptions in SSRS. Typically, Reporting service is used to view reports. However, most users would prefer to receive the report to their inbox in the preferred report format, such as Word, Excel, or PDF in a preferred time. Further, you might want these reports to be delivered to a file share. Let us see how we can achieve these options using Subscriptions in SSRS and what are the challenges and pre-configurations.

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Example of SSAS Dimension Hierachies from Sale sterritory Dimension.

Enhancing Data Analytics with SSAS Dimension Hierarchies

July 22, 2020 by

Introduction

This article will discuss how SSAS Dimension Hierarchies can be used to analyze data much efficiently. If you are a data analyst, you want to start the analysis with a higher hierarchy. Then navigate the narrow attributes when required. For example, it will be better to start with analyzing revenue by year. If you need to analyze further into the data, you can choose the needed year and expand the Quarter -> Month, respectively. Let us see how we can create SSAS Dimension Hierarchies in OLAP Cubes to suit different requirements.

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Creating OLAP Perspectives

Improve readability with SSAS Perspectives

July 9, 2020 by

Introduction

In this article, we will be looking at a feature of SQL Server Analysis Service (SSAS) OLAP Cube that is SSAS Perspectives. We discussed creating SSAS OLAP Cubes in a previous article: OLAP Cubes in SQL Server. In an SSAS OLAP cube, there can be a large number of measures, dimensions and dimension attributes. The following screenshot is the star schema for the selected example that was created from the AdventureWorksDW sample database that can be visible at Data Source View.

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