This document discusses data mining in SQL Server 2008. It provides an overview of different types of data analysis including ad-hoc querying, reporting, OLAP cubes, and data mining. It then describes how data mining algorithms like classification, regression, and association analysis are used to explore data, find patterns, and make predictions. It also outlines the typical data mining process and highlights new features and algorithms in SQL Server 2008 for time series analysis, market basket analysis, churn analysis, and more.
AORTA BI Solutions is specialized in implementing the Oracle BI Suite. The BI Server is the integrated platform to achieve al the necessary business requirements.
Rick van der Lans referred to it. He calls the BI Server an good example of which he calls the Data Delivery Platform.
AORTA BI Solutions is specialized in implementing the Oracle BI Suite. The BI Server is the integrated information platform the suite is build on. Many people don't know it, but it's one of the best technologies Oracle has ever acquired.
Creating a Tabular Model Using SQL Server 2012 Analysis ServicesCode Mastery
At Code Mastery Boston Steve Hughes, Principal Consultant at Magenic, highlights: Basics of SQL Server 2012 Analysis Services, Multidimensional Model, VS PowerPivot, Creating a Tabular Model
AORTA BI Solutions is specialized in implementing the Oracle BI Suite. The BI Server is the integrated platform to achieve al the necessary business requirements.
Rick van der Lans referred to it. He calls the BI Server an good example of which he calls the Data Delivery Platform.
AORTA BI Solutions is specialized in implementing the Oracle BI Suite. The BI Server is the integrated information platform the suite is build on. Many people don't know it, but it's one of the best technologies Oracle has ever acquired.
Creating a Tabular Model Using SQL Server 2012 Analysis ServicesCode Mastery
At Code Mastery Boston Steve Hughes, Principal Consultant at Magenic, highlights: Basics of SQL Server 2012 Analysis Services, Multidimensional Model, VS PowerPivot, Creating a Tabular Model
The Developer Data Scientist – Creating New Analytics Driven Applications usi...Microsoft Tech Community
The developer world is changing as we create and generate new data patterns and handling processes within our applications. Additionally, with the massive interest in machine learning and advanced analytics how can we as developers build intelligence directly into our applications that can integrate with the data and data paths we are creating? The answer is Azure Databricks and by attending this session you will be able to confidently develop smarter and more intelligent applications and solutions which can be continuously built upon and that can scale with the growing demands of a modern application estate.
By using a Data Lake, you no longer need to worry about structuring or transforming data before storing it. A Data Lake on AWS enables your organization to more rapidly analyze data, helping you quickly discover new business insights. Join us for our webinar to learn about the benefits of building a Data Lake on AWS and how your organization can begin reaping their rewards. In this session, we will share methodology for implementing a Data Lake on AWS and best practices for getting the most from your Data Lake.
Speaker: Russell Nash,
APAC Solution Architect, DW, AWS APAC
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
RDX Insights Presentation - Microsoft Business IntelligenceChristopher Foot
May's RDX Insights Series Presentation focuses on Microsoft's BI products. We begin with an overview of Power BI, SSIS, SSAS and SSRS and how the products integrate with each other. The webinar continues with a detailed discussion on how to use Power BI to capture, model, transform, analyze and visualize key business metrics. We’ll finish with a Power BI demo highlighting some of its most beneficial and interesting features.
Database Week at the San Francisco Loft
What is Database Freedom?
How AWS can help you unshackle and achieve transformation. Are you operating with old world databases?Discover Database Freedom with AWS.
Speaker: Ben Willett - Solutions Architect, AWS
Java Developers, make the database work for you (NLJUG JFall 2010)Lucas Jellema
The general consensus among Java developers has evolved from a dogmatic strive for database independence to a much more pragmatic wish to leverage the power of the database. This session demonstrates some of the (hidden) powers of the database and how these can be utilized from Java applications using either straight JDBC or working through JPA. The Oracle database is used as example: SQL for Aggregation and Analysis, Flashback Queries for historical comparison and trends, Virtual Private Database, complex validation, PL/SQL and collections for bulk data manipulation, view and instead-of triggers for data model morphing, server push of relevant data changes, edition based redefinition for release management.
- overview of role of database in JEE architecture (and a little history on how the database is perceived through the years)
- discussion on the development of database functionality
- demonstration of some powerful database features
- description of how we leveraged these features in our JSF (RichFaces)/JPA (Hibernate) application
- demo of web application based on these features
- discussion on how to approach the database
The Developer Data Scientist – Creating New Analytics Driven Applications usi...Microsoft Tech Community
The developer world is changing as we create and generate new data patterns and handling processes within our applications. Additionally, with the massive interest in machine learning and advanced analytics how can we as developers build intelligence directly into our applications that can integrate with the data and data paths we are creating? The answer is Azure Databricks and by attending this session you will be able to confidently develop smarter and more intelligent applications and solutions which can be continuously built upon and that can scale with the growing demands of a modern application estate.
By using a Data Lake, you no longer need to worry about structuring or transforming data before storing it. A Data Lake on AWS enables your organization to more rapidly analyze data, helping you quickly discover new business insights. Join us for our webinar to learn about the benefits of building a Data Lake on AWS and how your organization can begin reaping their rewards. In this session, we will share methodology for implementing a Data Lake on AWS and best practices for getting the most from your Data Lake.
Speaker: Russell Nash,
APAC Solution Architect, DW, AWS APAC
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
RDX Insights Presentation - Microsoft Business IntelligenceChristopher Foot
May's RDX Insights Series Presentation focuses on Microsoft's BI products. We begin with an overview of Power BI, SSIS, SSAS and SSRS and how the products integrate with each other. The webinar continues with a detailed discussion on how to use Power BI to capture, model, transform, analyze and visualize key business metrics. We’ll finish with a Power BI demo highlighting some of its most beneficial and interesting features.
Database Week at the San Francisco Loft
What is Database Freedom?
How AWS can help you unshackle and achieve transformation. Are you operating with old world databases?Discover Database Freedom with AWS.
Speaker: Ben Willett - Solutions Architect, AWS
Java Developers, make the database work for you (NLJUG JFall 2010)Lucas Jellema
The general consensus among Java developers has evolved from a dogmatic strive for database independence to a much more pragmatic wish to leverage the power of the database. This session demonstrates some of the (hidden) powers of the database and how these can be utilized from Java applications using either straight JDBC or working through JPA. The Oracle database is used as example: SQL for Aggregation and Analysis, Flashback Queries for historical comparison and trends, Virtual Private Database, complex validation, PL/SQL and collections for bulk data manipulation, view and instead-of triggers for data model morphing, server push of relevant data changes, edition based redefinition for release management.
- overview of role of database in JEE architecture (and a little history on how the database is perceived through the years)
- discussion on the development of database functionality
- demonstration of some powerful database features
- description of how we leveraged these features in our JSF (RichFaces)/JPA (Hibernate) application
- demo of web application based on these features
- discussion on how to approach the database
Today organizations find themselves in a data rich world with a growing need for increased agility and accessibility of all this data for analysis and deriving keen insights to drive strategic decisions. Creating a data lake helps you to manage all the disparate sources of data you are collecting, in its original format and extract value. In this session learn how to architect and implement an Analytics Data Lake. Hear customer examples of best practices and learn from their architectural blueprints.
Introduction to SQL Server Analysis services 2008Tobias Koprowski
This is my presentation from 17th Polish SQL server User Group Meeting in Wroclaw. It\'s first part of Quadrology Bussiness Intelligence for ITPros Cycle.
The concept about SAS software and it high end tools.
Stay connected for SAS programming Keywords.
Please not this uploaded ppt is not a copy right of any anonymous,this were created by Sushil Kasar for his basic learnings' and sharing Knowledge activities.
Regards,
Sushil & team.
AWS re:Invent 2016: How to Build a Big Data Analytics Data Lake (LFS303)Amazon Web Services
For discovery-phase research, life sciences companies have to support infrastructure that processes millions to billions of transactions. The advent of a data lake to accomplish such a task is showing itself to be a stable and productive data platform pattern to meet the goal. We discuss how to build a data lake on AWS, using services and techniques such as AWS CloudFormation, Amazon EC2, Amazon S3, IAM, and AWS Lambda. We also review a reference architecture from Amgen that uses a data lake to aid in their Life Science Research.
This presentation contains following slides,
Introduction To OLAP
Data Warehousing Architecture
The OLAP Cube
OLTP Vs. OLAP
Types Of OLAP
ROLAP V/s MOLAP
Benefits Of OLAP
Introduction - Apache Kylin
Kylin - Architecture
Kylin - Advantages and Limitations
Introduction - Druid
Druid - Architecture
Druid vs Apache Kylin
References
For any queries
Contact Us:- argonauts007@gmail.com
"Conceptually, a data lake is a flat data store to collect data in its original form, without the need to enforce a predefined schema. Instead, new schemas or views are created “on demand”, providing a far more agile and flexible architecture while enabling new types of analytical insights. AWS provides many of the building blocks required to help organizations implement a data lake. In this session, we will introduce key concepts for a data lake and present aspects related to its implementation. We will discuss critical success factors, pitfalls to avoid as well as operational aspects such as security, governance, search, indexing and metadata management. We will also provide insight on how AWS enables a data lake architecture.
A data lake is a flat data store to collect data in its original form, without the need to enforce a predefined schema. Instead, new schemas or views are created ""on demand"", providing a far more agile and flexible architecture while enabling new types of analytical insights. AWS provides many of the building blocks required to help organizations implement a data lake. In this session, we introduce key concepts for a data lake and present aspects related to its implementation. We discuss critical success factors and pitfalls to avoid, as well as operational aspects such as security, governance, search, indexing, and metadata management. We also provide insight on how AWS enables a data lake architecture. Attendees get practical tips and recommendations to get started with their data lake implementations on AWS."
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
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Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
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Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
2. Types of analysis
• Ad-hoc query/Reporting/Analysis
– What is the purpose?
• Simple reports
• Key Performance Indicators
• OLAP cubes – Slice & Dice
– In Real time - What happens now?
• Events/Triggers
• Data Mining
– How do we do it?
– What happens?
3. What does Data Mining Do?
Explores
Your Data
Finds
Patterns
Performs
Predictions
4. Data Mining Algorithms
• Classification
• Regression
• Segmentation
• Association
• Forecasting
• Text Analysis
• Advanced Data Exploration
6. Data Mining Process
SSAS
(OLAP)
Business Data
DSV
Understanding Understanding
SSIS
SSAS
Data
Data (OLAP)
Preparation
SSIS
SSAS(OLAP)
SSRS Deployment
Flexible APIs SSAS
Modeling (Data
Mining)
Evaluation
www.crisp-dm.org
7. Data Mining in SQL Server 2008
• New algorithms developed in conjunction
with Microsoft Research
• Data mining is made accessible and easy to
use through integrated user interface, cross-
product integration and familiar, standard APIs
• Complete framework for building and
deploying intelligent applications on the fly
• Integration into the cloud.
8. Top New Features in SQL Server 2008
• Test multiple data mining models simultaneously with statistical
scores of error and accuracy and confirm their stability with cross
validation
• Build multiple, incompatible mining models within a single
structure; apply model analysis over filtered data; query against
structure data to present complete information, all enabled by
enhanced mining structures
• Combine the best of both worlds by blending optimized near-term
predictions (ARTXP) and stable long-term predictions (ARIMA) with
Better Time Series Support
• Discover the relationship between items that are frequently
purchased together by using Shopping Basket Analysis; generate
interactive forms for scoring new cases with Predictive Calculator,
delivered with Microsoft SQL Server 2008 Data Mining Add-ins for
Office 2007
9. Rich and Innovative Algorithms
• Benefit from many rich and innovative data mining algorithms, most developed by Microsoft Research to
support common business problems promptly and accurately.
• Market Basket Analysis - Discover which items tend to be bought together to create recommendations on-
the-fly and to determine how product placement can directly contribute to your bottom line
• Churn Analysis - Anticipate customers who may be considering canceling their service and identify benefits
that will keep them from leaving
• Market Analysis - Define market segments by automatically grouping similar customers together. Use
these segments to seek profitable customers
• Forecasting - Predict sales and inventory amounts and learn how they are interrelated to foresee
bottlenecks and improve performance
• Data Exploration - Analyze profitability across customers, or compare customers who prefer different
brands of the same product to discover new opportunities
• Unsupervised Learning - Identify previously unknown relationships between various elements of your
business to better inform your decisions
• Web Site Analysis - Understand how people use your Web site and group similar usage patterns to offer a
better experience
• Campaign Analysis - Spend marketing dollars more effectively by targeting the customers most likely to
respond to a promotion
• Information Quality - Identify and handle anomalies during data entry or data loading to improve the
quality of information
• Text Analysis - Analyze feedback to find common themes and trends that concern your customers or
employees, informing decisions with unstructured input
10. Value of Data Mining
Business Knowledge
SQL Server 2008
Business value
Data Mining
OLAP
Reports (Adhoc)
Reports (static)
Simple Complex
Usability
11. Data Mining User Interface
• SQL Server BI Development Studio
– Environment for creation and data exploration
– Data Mining projects in Visual Studio solutions, tightly
integrated
– Source Control Integration
• SQL Server Management Studio
– One tool for all administrative tasks
– Manage, view and query mining models
12. BI Integration
• Integration Services
– Data Mining processing and results integrate
directly in IS pipeline
• OLAP
– Processing of mining models directly from
cubes
– Use of mining results as dimensions
• Reporting Services
– Embed Data Mining results directly in
Reporting Services Reports
13. Applied Data Mining
• Make Decisions without Coding
– Learn business rules directly from data
• Client Customization
– Learn logic customized for each client
• Automatic Update
– Data mining application logic updated by model re-
processing
– Applications do not need to be rewritten, recompiled, re-
deployed
14. Server Mining Architecture
BI Dev Your Application
Studio
(Visual
Studio) OLE DB/ ADOMD/ XMLA
App
Deploy Data
Analysis Services Mining Model
Server
Data Mining Algorithm Data
Source
15. Data Mining EXtensions
• OLE DB for Data Mining specification
– Now part of XML/A specification
– See www.xmla.org for XML/A details
• Connect to Analysis Server
– OLEDB, ADO, ADO.Net, ADOMD.Net, XMLA
Dim cmd as ADOMD.Command
Dim reader as ADOMD.DataReader
Cmd.Connection = conn
Set reader =
Cmd.ExecuteReader(“Select
Predict(Gender)…”)
16. Typical DM Process Using DMX
Define a model:
CREATE MINING MODEL ….
Data Mining
Train a model: Management System
INSERT INTO dmm …. (DMMS)
Training Data
Prediction using a model: Mining Model
SELECT …
FROM dmm PREDICTION JOIN …
Prediction Input Data
17. DMX Commands
• Definition (DDL)
– CREATE – Make new model
– SELECT INTO – Create model by copying existing
– EXPORT – Save model as .abf file
– IMPORT – Retrieve model from .abf file
• Manipulation (DML)
– INSERT INTO – Train model
– UPDATE – Change content of model
– DELETE – Clear content
– SELECT – Browse model
18. DMX SELECT Elements
• SELECT [FLATTENED] [TOP] <columns>
• FROM <model>
• PREDICTION JOIN <table>
• ON <mapping>
• WHERE <filter>
• ORDER BY <sort expression>
– Use query builder to create SELECT statement
19. Training a DM Model: Simple
INSERT INTO CollegePlanModel
(StudentID, Gender, ParentIncome,
Encouragement, CollegePlans)
OPENROWSET(‘<provider>’, ‘<connection>’,
‘SELECT StudentID,
Gender,
ParentIncome,
Encouragement,
CollegePlans
FROM CollegePlansTrainData’)
20. Prediction Using a DM Model
• PREDICTION JOIN
SELECT t.ID, CPModel.Plan
FROM CPModel PREDICTION JOIN
OPENQUERY(…,„SELECT * FROM NewStudents‟) AS t
ON CPModel.Gender = t.Gender AND
CPModel.IQ = t.IQ
21. Visit more self help tutorials
• Pick a tutorial of your choice and browse
through it at your own pace.
• The tutorials section is free, self-guiding and
will not involve any additional support.
• Visit us at www.dataminingtools.net