№ files_lp_3_process_9_27722
File format: docx
Character count: 51025
File size: 755 KB
Technical walkthrough article outlining the automated creation, processing, prediction generation, and reporting of multiple related data mining models within Microsoft SQL Server Integration Services and associated Analysis Services and Reporting Services components.
Year:
2011
Publication Date:
July 2011
Title:
SQL Server Technical Article
Topic:
Data mining and model automation
Product:
Microsoft SQL Server Integration Services
Applicable To:
SQL Server 2008 R2; SQL Server 2008; SQL Server 2005
Author:
Jeannine Takaki
Technical Reviewer:
Raman Iyer
Publisher:
Microsoft
Document Type:
Technical article
Audience:
Data analysts and data mining practitioners
Related Components:
SQL Server Analysis Services; SQL Server Reporting Services; Business Intelligence Development Studio; Data Mining Client Add-in for Microsoft Excel
Copyright:
© 2011 Microsoft. All rights reserved.
Price: 8 / 10 USD
The file will be delivered to the email address provided at checkout within 12 hours.
The file will be delivered to the email address provided at checkout within 12 hours.
Don’t have cryptocurrency yet?
You can still complete your purchase in a few minutes:- Buy Crypto in a trusted app (Coinbase, Kraken, Cash App or any similar service).
- In the app, tap Send.
- Select network, paste our wallet address.
- Send the exact amount shown above.
The final amount may vary slightly depending on the payment method.
The file will be sent to the email address provided at checkout within 24 hours.
The product description is provided for reference. Actual content and formatting may differ slightly.
Year:
2011
Region / city:
Global
Topic:
Business process automation
Document type:
Technical guide
Organization / institution:
Microsoft
Author:
Microsoft
Target audience:
Business analysts, IT professionals, developers, companies using Microsoft Dynamics AX 2012
Period of validity:
Not specified
Approval date:
Not specified
Modification date:
Not specified
Title of research:
Automating patient inhaler technique when using pressurised Metered Dose Inhalers: testing the functionality and impact of the aflo™ digital respiratory management platform in a randomised controlled trial in a primary care setting
Type of document:
Participant information sheet
Study design:
Randomised controlled trial
Setting:
Primary care
Target population:
Children aged 5 years or over with a diagnosis of asthma
Inclusion criteria:
Diagnosis of asthma; confirmed suitable by GP; access to smartphone and WIFI/4G; currently prescribed a spacer; adherence or symptom control issues
Intervention:
aflo™ digital respiratory management platform and inhaler device
Control:
Standard care
Study duration:
24 weeks
Appointments:
Three visits (baseline, 12 weeks, 24 weeks)
Procedures:
Questionnaires; inhaler technique demonstration; blood pressure measurement; lung function test; spirometry data access; blood sample collection
Sample collection:
Up to 8 ml blood at first appointment
Funding body:
Respiratory Analytics Ltd
Ethics approval:
West Midlands - Edgbaston Research Ethics Committee; MHRA
Compensation:
Travel reimbursement and £20 voucher
Data handling:
Anonymised data analysis; GP access to results
Year:
2023
Region / City:
International Space Station
Topic:
Microbial adaptation, Experimental evolution, Automation
Document Type:
Research Paper
Author:
Dhami, K. Griffis, C. Hergenradger, C. Govinda Raj, V. Singh, D. Gentry
Target Audience:
Researchers in microbial biology and space science
Period of Action:
Ongoing
Approval Date:
N/A
Modification Date:
N/A
Automating the raw data to model input process: an open Python package for wastewater treatment data
Year:
2013
Location:
Eindhoven, The Netherlands
Subject:
Wastewater treatment, data analysis
Document type:
Research article / software description
Institution:
Ghent University, Waterschap De Dommel, Delft University of Technology
Authors:
C. De Mulder, T. Flameling, J. Langeveld, Y. Amerlinck, S. Weijers, I. Nopens
Target audience:
Researchers and practitioners in wastewater modelling
Software:
Python package for data reconciliation and analysis
Data source:
Online high-frequency influent data from WWTP
Methodology:
Data filtering, interpolation, model-based gap filling
Implementation:
Jupyter Notebook environment
Availability:
To be published on GitHub
Year:
2012
Region / City:
N/A
Topic:
Data Warehouse Architecture
Document Type:
Technical Article
Organization / Institution:
Microsoft
Authors:
Eric Kraemer, Mike Bassett, Eric Lemoine, Dave Withers
Target Audience:
IT planners, architects, DBAs, business intelligence users
Period of validity:
N/A
Approval Date:
March 2012
Date of Changes:
N/A
Year:
2013
Region / City:
Global
Topic:
SQL Server, Plan Caching, Recompilation
Document Type:
Technical Article
Organization / Institution:
Microsoft
Author:
Greg Low, SQL Down Under
Target Audience:
SQL Server developers, database administrators, and those migrating to SQL Server 2012
Period of Application:
SQL Server 2012
Approval Date:
March 2013
Date of Changes:
Not specified
Note:
Year
Topic:
SQL Server, Availability Groups, Listener Configuration
Document Type:
Technical Guide
Target Audience:
Database Administrators, IT Professionals
Keywords:
SQL Server, Always On, Listener, Availability Group, Failover, Read-Only Routing
Product:
SQL Account
Document type:
Software release notes
Versions covered:
5.2025.1058.890–5.2026.1064.891
Release dates:
November 21, 2025 – January 5, 2026
Database versions:
220, 221
Main components:
Database, AI Easyscan, MyInvois (E-Invoice MY), InvoiceNow (Peppol SG), Ecommerce, Mobile Connect, Fixed Asset, Approval, Reporting
Regions referenced:
Singapore, Malaysia
Standards referenced:
Peppol, UUID, GST-SG, E-Invoice MY
Issuing organization:
SQL Account
Year:
2011
Note:
Region / City
Topic:
SQL Server, Database Mirroring, Transactional Replication
Document Type:
White Paper
Organization / Institution:
Microsoft Corporation
Author:
Gopal Ashok, Paul S. Randal
Target Audience:
Database Administrators, SQL Server professionals
Year:
2009
Region / City:
Global
Topic:
Disk Partition Alignment
Document Type:
White Paper
Author:
Jimmy May, Denny Lee
Target Audience:
SQL Server Administrators, IT Professionals
Period of validity:
Ongoing
Approval Date:
May 2009
Modification Date:
N/A
Year:
2008
Region / city:
Global
Topic:
SQL Server Licensing
Document Type:
Technical Guide
Organization / Institution:
Microsoft
Author:
Microsoft
Target Audience:
IT Professionals, Database Administrators, Software Licensors
Validity Period:
Not specified
Approval Date:
July 2008
Amendment Date:
Not specified
Year:
2014
Applies to:
SQL Server 2012 (including 2012 SP1), SQL Server 2014
Type of document:
White Paper / Technical Guide
Authors:
Karan Gulati, Jon Burchel
Editor:
Jeannine Takaki
Contributors and Technical Reviewers:
Akshai Mirchandani, Siva Harinath, Lisa Liu
Organization:
Microsoft Corporation
Audience:
Business Intelligence Developers
Content:
Performance tuning techniques for OLAP solutions and design patterns for scalable cubes
Copyright:
© 2014 Microsoft Corporation
Year:
2014
Region / City:
Global
Topic:
SQL Server, Azure SQL Database, Idle Connection Resiliency
Document Type:
Technical Article
Organization / Institution:
Microsoft
Author:
Luiz Fernando Santos, Matt Neerincx
Target Audience:
Developers, IT professionals
Effective Period:
N/A
Approval Date:
March 2014
Date of Changes:
N/A
Year:
2013
Note:
Region / City
Topic:
Performance tuning, SQL Server 2012, Tabular Models
Document Type:
Technical Article
Organization:
Microsoft
Author:
John Sirmon, Greg Galloway, Cindy Gross, Karan Gulati
Target Audience:
IT professionals, Data Engineers, Analysts
Summary:
This document describes techniques and strategies for optimizing performance in tabular models within SQL Server 2012 Analysis Services, focusing on areas such as query tuning, partitioning, and server configuration.
Authors:
Cathy Dumas, Kasper de Jonge
Contributors:
Marius Dumitru, Akshai Mirchandani, Bob Meyers, Siva Harinath, Bradley Ouellette, Greg Galloway, Howie Dickerman
Technical Reviewers:
Nick Medveditskov, Edward Melomed, Owen Duncan, Dave Wickert, Thomas Ivarsson
Published:
April 2012
Updated:
April 2016
Applies to:
SQL Server 2012, SQL Server 2014, SQL Server 2016, Azure Analysis Services, Power BI
Document type:
Technical article
Topic:
Tabular BI security model, role management, dynamic security
Intended audience:
BI professionals, SQL Server and Power BI users
Content includes:
Examples, implementation guidance, sample data files, row-level security techniques
Year:
2009
Applies to:
SQL Server 2008
Type of Document:
Technical Article / White Paper
Authors:
Sunil Agarwal, Boris Baryshnikov, Keith Elmore, Juergen Thomas, Kun Cheng, Burzin Patel
Technical Reviewers:
Jerome Halmans, Fabricio Voznika, George Reynya
Publisher:
Microsoft Corporation
Publication Date:
March 2009
Topics:
Database performance, SQL Server troubleshooting, resource bottlenecks, memory and I/O optimization, tempdb management, query performance
Intended Audience:
Database administrators, IT professionals
Tools Covered:
SQL Server Profiler, Performance Monitor, Dynamic Management Views, Extended Events, Data Collector
Year:
2011
Region / City:
Global
Topic:
Security and Compliance, Database Administration
Document Type:
White Paper
Organization / Institution:
Microsoft Corporation
Author:
Lara Rubbelke
Contributor:
Kathi Kellenberger
Reviewers:
Jack Richins, Darmadi Komo
Target Audience:
Data platform managers, application owners, Database Administrators
Applicable Products:
SQL Server 2008, SQL Server 2008 R2
Date of Approval:
April 2011
Modification Date:
Not specified
Year:
2012
Note:
Region / City
Topic:
Security, SQL Server, Best Practices
Document Type:
White Paper
Organization / Institution:
Microsoft Corporation
Author:
Bob Beauchemin
Target Audience:
Operational DBAs
Approval Date:
January 2012
Description:
This document outlines best practices for securing SQL Server 2012, specifically for operational and administrative tasks, focusing on security configuration, policy-based management, and server role management.
Year:
2011
Region / City:
N/A
Topic:
Data Warehousing, Business Intelligence
Document Type:
Technical Article
Organization / Institution:
Microsoft
Author:
Warren Thornthwaite
Target Audience:
Data warehouse and business intelligence professionals, IT architects
Validity Period:
N/A
Approval Date:
June 2011
Date of Modifications:
N/A
Year:
2026
Region / city:
United Kingdom
Topic:
Intellectual property, AI training, copyright exceptions
Document type:
Government consultation annex
Organization / institution:
Intellectual Property Office (IPO)
Authors:
Not specified
Target audience:
Policymakers, stakeholders in AI and copyright
Policy period:
Current and proposed regulations for TDM and CGW
Consultation stage:
Analysis of short-list policy options and regulatory impacts