The possibilities of DATPROF Subet en DATPROF Privacy. For Subsetting databases en masking databases. To improve testing of software and to comply to data privacy regulations
Ray Scott - Agile Solutions – Leading with Test Data Management - EuroSTAR 2012TEST Huddle
EuroSTAR Software Testing Conference 2012 presentation on Agile Solutions – Leading with Test Data Management by Ray Scott. See more at: http://conference.eurostarsoftwaretesting.com/past-presentations/
Multidimensional Challenges and the Impact of Test Data ManagementCognizant
Test data management (TDM) is vital for quality assurance (QA) functions to best handle the many cha;l;enges associated with data security, release management, batch processing, data masking and fencing.
Testing(Manual or Automated) depends a lot on the test data being used. In a fast paced dynamic agile development quality of data being used for testing is paramount for success.
Data warehouses have become a popular mechanism for collecting, organizing, and making information readily available for strategic decision making. The ability to review historical trends and monitor near real-time operational data has become a key competitive advantage for many organizations. Yet the methods for assuring the quality of these valuable assets are quite different from those of transactional systems. Ensuring that the appropriate testing is performed is a major challenge for many enterprises. Geoff Horne has led a number of data warehouse testing projects in both the telecommunications and ERP sectors. Join Geoff as he shares his approaches and experiences, focusing on the key “uniques” of data warehouse testing including methods for assuring data completeness, monitoring data transformations, and measuring quality. He also explores the opportunities for test automation as part of the data warehouse process, describing how it can be harnessed to streamline and minimize overhead.
Ray Scott - Agile Solutions – Leading with Test Data Management - EuroSTAR 2012TEST Huddle
EuroSTAR Software Testing Conference 2012 presentation on Agile Solutions – Leading with Test Data Management by Ray Scott. See more at: http://conference.eurostarsoftwaretesting.com/past-presentations/
Multidimensional Challenges and the Impact of Test Data ManagementCognizant
Test data management (TDM) is vital for quality assurance (QA) functions to best handle the many cha;l;enges associated with data security, release management, batch processing, data masking and fencing.
Testing(Manual or Automated) depends a lot on the test data being used. In a fast paced dynamic agile development quality of data being used for testing is paramount for success.
Data warehouses have become a popular mechanism for collecting, organizing, and making information readily available for strategic decision making. The ability to review historical trends and monitor near real-time operational data has become a key competitive advantage for many organizations. Yet the methods for assuring the quality of these valuable assets are quite different from those of transactional systems. Ensuring that the appropriate testing is performed is a major challenge for many enterprises. Geoff Horne has led a number of data warehouse testing projects in both the telecommunications and ERP sectors. Join Geoff as he shares his approaches and experiences, focusing on the key “uniques” of data warehouse testing including methods for assuring data completeness, monitoring data transformations, and measuring quality. He also explores the opportunities for test automation as part of the data warehouse process, describing how it can be harnessed to streamline and minimize overhead.
Automate data warehouse etl testing and migration testing the agile wayTorana, Inc.
Data Warehouse, ETL & Migration projects are exposed to huge financial risks due to lack of QA automation. At iCEDQ, we suggest the agile rules based testing approach for all data integration projects.
Management & streamlining of test data is more than important and test data management remains a critical component in the testing life cycle for software & apps.
Test data management or TDM, facilitates test data during various phases of a software development life cycle. The data consumed, tested & modified is constantly put to use during the complete software cycle.
The evolution of Test Data Management into a comprehensive service ensures that the need for relevant data during various phases of the software life cycles are taken care of pushing faster go-market times.
Get More Insight at:
http://softwaretestingsolution.com/blog/test-data-management-managed-service-software-quality-assurance/
Test Data Management and Its Role in DevOpsTechWell
Do you often have to wait for the availability of the right test data to complete your testing? Now imagine you are using continuous integration and continuous delivery with agile and DevOps, and your test data is not available when you need it. This is a challenge and a bottleneck for the rollout of true DevOps. The key to efficient test data management (TDM) is to streamline and automate the test data management process to deliver the test data in minutes, use correct datasets for test improvement and coverage, and secure the test data automatically, enabling shorter test cycles. Join Sunil Sehgal as he shares how to automate test data creation by retrieving and storing data with a game-changing data model—The Logical Unit. Sunil shows how to look at data a different way—storing and retrieving it based on business logic, thus the name Logical Unit. Join Sunil as he explains how this allows the business to easily design TDM’s base schema according to their needs, rather than trying to fit them into a pre-defined structure.
Testing the Data Warehouse―Big Data, Big ProblemsTechWell
Data warehouses have become a popular mechanism for collecting, organizing, and making information readily available for strategic decision making. The ability to review historical trends and monitor near real-time operational data has become a key competitive advantage for many organizations. Yet the methods for assuring the quality of these valuable assets are quite different from those of transactional systems. Ensuring that the appropriate testing is performed is a major challenge for many enterprises. Geoff Horne has led a number of data warehouse testing projects in both the telecommunications and ERP sectors. Join Geoff as he shares his approaches and experiences, focusing on the key “uniques” of data warehouse testing including methods for assuring data completeness, monitoring data transformations, and measuring quality. He also explores the opportunities for test automation as part of the data warehouse process, describing how it can be harnessed to streamline and minimize overhead.
Data summit connect fall 2020 - rise of data opsRyan Gross
Data governance teams attempt to apply manual control at various points for consistency and quality of the data. By thinking of our machine learning data pipelines as compilers that convert data into executable functions and leveraging data version control, data governance and engineering teams can engineer the data together, filing bugs against data versions, applying quality control checks to the data compilers, and other activities. This talk illustrates how innovations are poised to drive process and cultural changes to data governance, leading to order-of-magnitude improvements.
Transforming Business Intelligence TestingMethod360
Learn how to strategically plan your manual and automated BI testing efforts so that it translates into a seamless and targeted tactical test execution phase leading to significant cost savings, increased reporting accuracy and greater business confidence.
Fraction ERP is design for small to medium sized manufacturing companies. Cloud hosted software for make to order or batch manufacturing businesses. Integration with Xero Accounts and Quickbooks Online.
Business critical data about your customers, products, operations and resources is everywhere. It is the oil that lubricates and fuels your business. Your data is propagating in real time across an ever-increasing number of channels and systems to an ever-larger number of stakeholders and decision makers. Ensuring that all this data is of sufficient quality, where and when it is created, updated, transported or stored has therefore become a mandate to manage risk and comply with regulations.
In this presentation, you'll learn how to turn your data into trusted assets:
- Standardize and unify your data across a heterogeneous landscape in a non-intrusive way
- Assess and monitor the quality of your data across internal, cloud, web and mobile applications
- Establish gatekeepers and rule-based controls to protect your information systems against errors that could cause erroneous decisions or process inefficiencies
Data Warehouse Testing: It’s All about the PlanningTechWell
Today’s data warehouses are complex and contain heterogeneous data from many different sources. Testing these warehouses is complex, requiring exceptional human and technical resources. So how do you achieve the desired testing success? Geoff Horne believes that it is through test planning that includes technical artifacts such as data models, business rules, data mapping documents, and data warehouse loading design logic. Wayne shares planning checklists, a test plan outline, concepts for data profiling, and methods for data verification. He demonstrates how to effectively create a test strategy to discover empty fields, missing records, truncated data, duplicate records, and incorrectly applied business rules—all of which can dramatically impact the usefulness of the data warehouse. Learn common pitfalls, which can cost your business hundreds of thousands of dollars or more, when test planning shortcuts are taken. If you work in an environment that often performs data warehouse testing without proper planning and technical skills, this session is for you.
Testing Big Data: Automated Testing of Hadoop with QuerySurgeRTTS
Are You Ready? Stepping Up To The Big Data Challenge In 2016 - Learn why Testing is pivotal to the success of your Big Data Strategy.
According to a new report by analyst firm IDG, 70% of enterprises have either deployed or are planning to deploy big data projects and programs this year due to the increase in the amount of data they need to manage.
The growing variety of new data sources is pushing organizations to look for streamlined ways to manage complexities and get the most out of their data-related investments. The companies that do this correctly are realizing the power of big data for business expansion and growth.
Learn why testing your enterprise's data is pivotal for success with big data and Hadoop. Learn how to increase your testing speed, boost your testing coverage (up to 100%), and improve the level of quality within your data - all with one data testing tool.
Deliver Trusted Data by Leveraging ETL TestingCognizant
We explore how extract, transform and load (ETL) testing with SQL scripting is crucial to data validation and show how to test data on a large scale in a streamlined manner with an Informatica ETL testing tool.
T2 Tech Group is a leader in the practical application of technology for healthcare and a range of other industries. Since its founding in 2006, T2 Tech has consistently delivered quality consulting and management advisory services to executives and IT leaders. Unlike many consulting firms, T2 Tech has no financial interest in vendor selection, freeing the company to focus completely on realizing client goals. The organization balances business and IT needs, uses a proven framework, can see projects from assessment to post-implementation, and practices transparency in everything they do.
15 Tips on Salesforce Data Migration - Naveen Gabrani & Jonathan OsgoodSalesforce Admins
Data Migration is an extremely important aspect of setting up a Salesforce instance. It is critical that the sanctity of data is maintained. Join us to hear fifteen tips based on learnings from different types of data migration projects.
Test Data Management: A Healthcare Industry Case StudyTechWell
As IT systems increase in both scale and complexity, delivering quality applications becomes more challenging. In addition to creating and executing test scenarios, testers need to create and maintain the test data that enables test execution. Test data management (TDM) creates and processes data in test environments using business knowledge and technology. Test data is created based on requirements provided from consumers. With TDM in your software delivery process, teams dependent on data can focus on creating and executing test scenarios instead of having to provision the data to run these tests. Shaheer Mohammed and Jatinder Singh present a case study that recaps the successful creation of a TDM team. They review what worked well, share lessons learned along the way, touch on the challenges of managing protected data in the health-care industry, and discuss innovative tools and processes that enabled their success.
"How to document your decisions", Dmytro Ovcharenko Fwdays
We will perform architecture kata around a proposed business case. We will review ADD in detail. How usually architecture vision document looks like. How to match your architecture drivers and proposed architecture decisions in architecture views. We will review what is ATAM and how to perform analysis of your decisions in the right way. And finally, we will create an architecture vision document from scratch.
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...Mihai Criveti
Automate your Data Science pipeline with Ansible, Python and Kubernetes - ODSC Talk
What is Data Science and the Data Science Landscape
Process and Flow
Understanding Data
The Data Science Toolkit
The Big Data Challenge
Cloud Computing Solutions
The rise of DevOps in Data Science
Automate your data pipeline with Ansible
Test Data Management 101—Featuring a Tour of CA Test Data Manager (Formerly G...CA Technologies
Ever wonder exactly how Test Data Manager (TDM) works and how you can maximize your TDM investment? In this session we will cover:
- What value does TDM provide organizations?
- What can CA Test Data Manager do to help?
This session will teach how you can maximize your investment.
For more information, please visit http://cainc.to/Nv2VOe
Automate data warehouse etl testing and migration testing the agile wayTorana, Inc.
Data Warehouse, ETL & Migration projects are exposed to huge financial risks due to lack of QA automation. At iCEDQ, we suggest the agile rules based testing approach for all data integration projects.
Management & streamlining of test data is more than important and test data management remains a critical component in the testing life cycle for software & apps.
Test data management or TDM, facilitates test data during various phases of a software development life cycle. The data consumed, tested & modified is constantly put to use during the complete software cycle.
The evolution of Test Data Management into a comprehensive service ensures that the need for relevant data during various phases of the software life cycles are taken care of pushing faster go-market times.
Get More Insight at:
http://softwaretestingsolution.com/blog/test-data-management-managed-service-software-quality-assurance/
Test Data Management and Its Role in DevOpsTechWell
Do you often have to wait for the availability of the right test data to complete your testing? Now imagine you are using continuous integration and continuous delivery with agile and DevOps, and your test data is not available when you need it. This is a challenge and a bottleneck for the rollout of true DevOps. The key to efficient test data management (TDM) is to streamline and automate the test data management process to deliver the test data in minutes, use correct datasets for test improvement and coverage, and secure the test data automatically, enabling shorter test cycles. Join Sunil Sehgal as he shares how to automate test data creation by retrieving and storing data with a game-changing data model—The Logical Unit. Sunil shows how to look at data a different way—storing and retrieving it based on business logic, thus the name Logical Unit. Join Sunil as he explains how this allows the business to easily design TDM’s base schema according to their needs, rather than trying to fit them into a pre-defined structure.
Testing the Data Warehouse―Big Data, Big ProblemsTechWell
Data warehouses have become a popular mechanism for collecting, organizing, and making information readily available for strategic decision making. The ability to review historical trends and monitor near real-time operational data has become a key competitive advantage for many organizations. Yet the methods for assuring the quality of these valuable assets are quite different from those of transactional systems. Ensuring that the appropriate testing is performed is a major challenge for many enterprises. Geoff Horne has led a number of data warehouse testing projects in both the telecommunications and ERP sectors. Join Geoff as he shares his approaches and experiences, focusing on the key “uniques” of data warehouse testing including methods for assuring data completeness, monitoring data transformations, and measuring quality. He also explores the opportunities for test automation as part of the data warehouse process, describing how it can be harnessed to streamline and minimize overhead.
Data summit connect fall 2020 - rise of data opsRyan Gross
Data governance teams attempt to apply manual control at various points for consistency and quality of the data. By thinking of our machine learning data pipelines as compilers that convert data into executable functions and leveraging data version control, data governance and engineering teams can engineer the data together, filing bugs against data versions, applying quality control checks to the data compilers, and other activities. This talk illustrates how innovations are poised to drive process and cultural changes to data governance, leading to order-of-magnitude improvements.
Transforming Business Intelligence TestingMethod360
Learn how to strategically plan your manual and automated BI testing efforts so that it translates into a seamless and targeted tactical test execution phase leading to significant cost savings, increased reporting accuracy and greater business confidence.
Fraction ERP is design for small to medium sized manufacturing companies. Cloud hosted software for make to order or batch manufacturing businesses. Integration with Xero Accounts and Quickbooks Online.
Business critical data about your customers, products, operations and resources is everywhere. It is the oil that lubricates and fuels your business. Your data is propagating in real time across an ever-increasing number of channels and systems to an ever-larger number of stakeholders and decision makers. Ensuring that all this data is of sufficient quality, where and when it is created, updated, transported or stored has therefore become a mandate to manage risk and comply with regulations.
In this presentation, you'll learn how to turn your data into trusted assets:
- Standardize and unify your data across a heterogeneous landscape in a non-intrusive way
- Assess and monitor the quality of your data across internal, cloud, web and mobile applications
- Establish gatekeepers and rule-based controls to protect your information systems against errors that could cause erroneous decisions or process inefficiencies
Data Warehouse Testing: It’s All about the PlanningTechWell
Today’s data warehouses are complex and contain heterogeneous data from many different sources. Testing these warehouses is complex, requiring exceptional human and technical resources. So how do you achieve the desired testing success? Geoff Horne believes that it is through test planning that includes technical artifacts such as data models, business rules, data mapping documents, and data warehouse loading design logic. Wayne shares planning checklists, a test plan outline, concepts for data profiling, and methods for data verification. He demonstrates how to effectively create a test strategy to discover empty fields, missing records, truncated data, duplicate records, and incorrectly applied business rules—all of which can dramatically impact the usefulness of the data warehouse. Learn common pitfalls, which can cost your business hundreds of thousands of dollars or more, when test planning shortcuts are taken. If you work in an environment that often performs data warehouse testing without proper planning and technical skills, this session is for you.
Testing Big Data: Automated Testing of Hadoop with QuerySurgeRTTS
Are You Ready? Stepping Up To The Big Data Challenge In 2016 - Learn why Testing is pivotal to the success of your Big Data Strategy.
According to a new report by analyst firm IDG, 70% of enterprises have either deployed or are planning to deploy big data projects and programs this year due to the increase in the amount of data they need to manage.
The growing variety of new data sources is pushing organizations to look for streamlined ways to manage complexities and get the most out of their data-related investments. The companies that do this correctly are realizing the power of big data for business expansion and growth.
Learn why testing your enterprise's data is pivotal for success with big data and Hadoop. Learn how to increase your testing speed, boost your testing coverage (up to 100%), and improve the level of quality within your data - all with one data testing tool.
Deliver Trusted Data by Leveraging ETL TestingCognizant
We explore how extract, transform and load (ETL) testing with SQL scripting is crucial to data validation and show how to test data on a large scale in a streamlined manner with an Informatica ETL testing tool.
T2 Tech Group is a leader in the practical application of technology for healthcare and a range of other industries. Since its founding in 2006, T2 Tech has consistently delivered quality consulting and management advisory services to executives and IT leaders. Unlike many consulting firms, T2 Tech has no financial interest in vendor selection, freeing the company to focus completely on realizing client goals. The organization balances business and IT needs, uses a proven framework, can see projects from assessment to post-implementation, and practices transparency in everything they do.
15 Tips on Salesforce Data Migration - Naveen Gabrani & Jonathan OsgoodSalesforce Admins
Data Migration is an extremely important aspect of setting up a Salesforce instance. It is critical that the sanctity of data is maintained. Join us to hear fifteen tips based on learnings from different types of data migration projects.
Test Data Management: A Healthcare Industry Case StudyTechWell
As IT systems increase in both scale and complexity, delivering quality applications becomes more challenging. In addition to creating and executing test scenarios, testers need to create and maintain the test data that enables test execution. Test data management (TDM) creates and processes data in test environments using business knowledge and technology. Test data is created based on requirements provided from consumers. With TDM in your software delivery process, teams dependent on data can focus on creating and executing test scenarios instead of having to provision the data to run these tests. Shaheer Mohammed and Jatinder Singh present a case study that recaps the successful creation of a TDM team. They review what worked well, share lessons learned along the way, touch on the challenges of managing protected data in the health-care industry, and discuss innovative tools and processes that enabled their success.
"How to document your decisions", Dmytro Ovcharenko Fwdays
We will perform architecture kata around a proposed business case. We will review ADD in detail. How usually architecture vision document looks like. How to match your architecture drivers and proposed architecture decisions in architecture views. We will review what is ATAM and how to perform analysis of your decisions in the right way. And finally, we will create an architecture vision document from scratch.
DevOps for Data Engineers - Automate Your Data Science Pipeline with Ansible,...Mihai Criveti
Automate your Data Science pipeline with Ansible, Python and Kubernetes - ODSC Talk
What is Data Science and the Data Science Landscape
Process and Flow
Understanding Data
The Data Science Toolkit
The Big Data Challenge
Cloud Computing Solutions
The rise of DevOps in Data Science
Automate your data pipeline with Ansible
Test Data Management 101—Featuring a Tour of CA Test Data Manager (Formerly G...CA Technologies
Ever wonder exactly how Test Data Manager (TDM) works and how you can maximize your TDM investment? In this session we will cover:
- What value does TDM provide organizations?
- What can CA Test Data Manager do to help?
This session will teach how you can maximize your investment.
For more information, please visit http://cainc.to/Nv2VOe
Linked Data for Information Extraction Challenge - Tasks and Results @ ISWC 2014Robert Meusel
The Linked Data for Information Extraction challenge explores aims at extracting structured data from Web pages. It is based on a subset of the Web Data Commons Microformats dataset.
For the challenge, original annotated pages are provided, as well as the triples extracted from them. Based on that information, participants have to design an Information extraction system for extracting that information from other web pages. In this year's challenge, we focus on hCard data, i.e., information about persons. The use case of such a system could be the assembly of a large database on person data.
The systems are evaluated on a test set of annotated web pages, from which all annotations have been removed. The participants have to extract triples from those pages and send in their resulting triple files. The submitted files are evaluated against the gold standard of the original triples, ranking the solutions by F-measure.
Case Study: Manheim Implements Test Data Management to Reduce Testing Time an...CA Technologies
At Manheim, CA Test Data Manager (formerly Grid-Tools Data Maker) is used to provide teams with the data they needed, when they needed it. In this session, learn how Manheim uses synthetic data generation to reduce human interaction by 80% in the data provisioning process and data subset to achieve low-cost, rapid extraction of test data from production databases.
For more information, please visit http://cainc.to/Nv2VOe
- Understand the principles behind the agile approach to software development
- Differentiate between the testing role in agile projects compared with the role of testers in non-agile projects
- Positively contribute as an agile team member focused on testing
- Appreciate the challenges and difficulties associated with the non-testing activities performed in an agile team
- Demonstrate a range of soft skills required by agile team members
Agile/Scrum best Practices to improve quality.If some testing finds some defects, lot of testing would find lot of defects and improve quality. This presentation talks about few testing best practices that an agile team should follow for quality PI.
According to our customer surveys and confirmed by industry statistics, manual testers spend 50-70% of their effort on finding and preparing appropriate test data. Considering the fact that manual testing still accounts for 80+% of test operation efforts, up to half (!) of the overall testing effort goes into dealing with test data.
Find out how Tosca Testsuite can help you to lower the maintenance effort of your test data and operating costs of your test environment while building an efficient test data management strategy.
OSI Referans Modeli ve Katmanları - Alican UzunhanMesut Güneş
OSI (Open System Interconnection) Referans Modeli ilk kez 1978 yılında ortaya çıkmış olup 1984 yılında Uluslararası Standartlar Örgütü (ISO) tarafından yeni düzenlemeyle geliştirilmiştir. Modelin amacı, temel olarak ağ üzerindeki iki bilgisayarın iletişiminin nasıl olacağını belirtir.
Bölüm 1: Giriş (Introduction)
Bölüm 2: Hata Ne Zaman Tespit Edilebilir? (When Can a Defect be Detected?)
Bölüm 3: Hata Raporu Alanları (Defect Report Fields)
Bölüm 4: Hata Sınıflandırma ( Defect Classification)
Bölüm 5: Kök Neden (Ana Neden) Analizi (Root Cause Analysis)
Bölüm 6: Soru Örnekleri
Bölüm 1: Spesifikasyona Dayalı Test Teknikleri (Specification-Based )
Bölüm 2: Denklik Paylarına Ayırma (Equivalence Partitioning)
Bölüm 3: Sınır Değer Analizi (Boundary Value Analysis)
Bölüm 4: Karar Tablosu (Decision Table Testing)
Bölüm 5: Durum Geçiş Testi (State Transition Testing)
Bölüm 6: Kullanım Seneryosu Testi (Use Case Testing)
Eğitim İçeriği
Bölüm 7: Örnek Soru ve Cevapları
Lauri Pietarinen - What's Wrong With My Test DataTEST Huddle
EuroSTAR Software Testing Conference 2008 presentation on What's Wrong With My Test Data by Lauri Pietarinen. See more at conferences.eurostarsoftwaretesting.com/past-presentations/
What is a Data Warehouse and How Do I Test It?RTTS
ETL Testing: A primer for Testers on Data Warehouses, ETL, Business Intelligence and how to test them.
Are you hearing and reading about Big Data, Enterprise Data Warehouses (EDW), the ETL Process and Business Intelligence (BI)? The software markets for EDW and BI are quickly approaching $22 billion, according to Gartner, and Big Data is growing at an exponential pace.
Are you being tasked to test these environments or would you like to learn about them and be prepared for when you are asked to test them?
RTTS, the Software Quality Experts, provided this groundbreaking webinar, based upon our many years of experience in providing software quality solutions for more than 400 companies.
You will learn the answer to the following questions:
• What is Big Data and what does it mean to me?
• What are the business reasons for a building a Data Warehouse and for using Business Intelligence software?
• How do Data Warehouses, Business Intelligence tools and ETL work from a technical perspective?
• Who are the primary players in this software space?
• How do I test these environments?
• What tools should I use?
This slide deck is geared towards:
QA Testers
Data Architects
Business Analysts
ETL Developers
Operations Teams
Project Managers
...and anyone else who is (a) new to the EDW space, (b) wants to be educated in the business and technical sides and (c) wants to understand how to test them.
EMC XtremIO and EMC Isilon scale-out architectures make them an ideal fit to handle the demanding Splunk requirements around intensive workloads. EMC brings the same enterprise-class data services to Splunk that earned them best of breed status across the board in area such Scale-Out NAS storage, data protection, compliance and performance tiering.
How healthy is your data?
Data health is a multi-dimensional indicator of the integrity and effectiveness of your organization's most valuable asset. It is something that is increasingly difficult to be sure of when your data is growing in size and complexity, and when your team is becoming more dispersed.
Get insight into your Big Data like never before with the Data Health Dashboards in QuerySurge, the leading Data Testing software. These dashboards will enable you to easily see trends in both your data and your team's performance.
In this slide deck, you will learn how to:
- Improve your data quality
- Reduce your costs & risks
- Accelerate your data testing cycles
- Share information with your team
- Gain a holistic view of the health of your data
To see the Webinar, please visit:
http://www.querysurge.com/solutions/data-warehouse-testing/improve-data-health
Big Data – Shining the Light on Enterprise Dark DataHitachi Vantara
Content stored for a business purpose is often without structure or metadata required to determine its original purpose. With Hitachi Data Discovery Suite and Hitachi Content Platform, businesses can uncover dark data that could be leveraged for better business insight and uncover compliance issues that could prevent business risks. View this session and learn: What is enterprise dark data? How can enterprise dark data impact business decisions? How can you augment your underutilized data and deliver more value? How can you decrease the headache and challenges created by dark data? For more information please visit: http://www.hds.com/products/file-and-content/
This presentation is prepared by one of our renowned tutor "Suraj"
If you are interested to learn more about Big Data, Hadoop, data Science then join our free Introduction class on 14 Jan at 11 AM GMT. To register your interest email us at info@uplatz.com
Testing the Data Warehouse―Big Data, Big ProblemsTechWell
Data warehouses have become a popular mechanism for collecting, organizing, and making information readily available for strategic decision making. The ability to review historical trends and monitor near real-time operational data has become a key competitive advantage for many organizations. Yet the methods for assuring the quality of these valuable assets are quite different from those of transactional systems. Ensuring that the appropriate testing is performed is a major challenge for many enterprises. Geoff Horne has led a number of data warehouse testing projects in both the telecommunications and ERP sectors. Join Geoff as he shares his approaches and experiences, focusing on the key “uniques” of data warehouse testing including methods for assuring data completeness, monitoring data transformations, and measuring quality. He also explores the opportunities for test automation as part of the data warehouse process, describing how it can be harnessed to streamline and minimize overhead.
The presentation of Bert Nienhuis given during the breakfast session at Sogeti Netherlands. It was a demonstration about DATPROF Privacy for data masking, data anonymization and data scrambling.
De Presentatie van Hilbrand Kikkers vanuit ITCG met DATPROF privacy over het anonimiseren van testdata. En de impact op het uitvoeren van een Privacy Impact Assesment. Deze presentatie is gegeven tijdens een bijeenkomst van het Privacy Paleis op de Europese Dag van de Privacy.
Test Tool Event van Sogeti | DATPROF Testdata Management DATPROF
De presentatie over Testdata Management, hoe kun je eenvoudig een test-database verkleinen en daarmee behoorlijk kosten besparen. En hoe en welke gegevens zou je moeten anonimiseren om te voldoen aan wet- en regelgevingen.
Testdata kennissessie: Pas op: Persoonsgegevens?!DATPROF
Presentatie van 12 december van DATPROF over haar testdata management oplossing. De concepten die achter DATPROF Subset en Privacy zitten en hoe er mogelijk kan worden voldaan aan wet- en regelgevingen.
De handout van de twee presentaties over datamasking gegeven tijdens TMAPdag 2013. Op welke wijze is testdata te ontdoen van privacy gevoelige informatie!
In het algemeen zijn er identificerende en kenmerkende gegevens. Kenmerkende gegevens zijn de gegevens die privacy-gevoelig zijn (banksaldo, ziekte, fraude), en in combinatie met identificerende gegevens(Naam, Adres, Woonplaats) ontstaat de noodzaak van anonimiseren(voor de wetgever, De Nederlandsche Bank, AFM, Concurrentie-gevoeligheid).
In deze presentatie is zichtbaar hoe relaties te ontdoen zijn van deze gegevens.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
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Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
6. Agile Development
• Building the right product
• Room for change
• Every 2-4 weeks working increments of the software
• Progress in development
7. How to test all these iterations?
And… what data to use?
8. Team 1 Team 2 Team 3
6 TB 500 GB
Production
10 GB
6 TB 500 GB
Test
10 GB 6 TB 500 GB
Development
10 GB
Total
19,53 TB
9. Team 1 Team 2 Team 3
6 TB 500 GB
Production
10 GB
6 TB 500 GB
Test
10 GB 6 TB 500 GB
Development
10 GB
Total
19,53 TB
Team 1 Team 2 Team 3
Test
Team 1 Team 2 Team 3
Development
10. Team 1 Team 2 Team 3
6 TB 500 GB
Production
10 GB
6 TB 500 GB
Development
10 GB
6 TB 500 GB
Test
10 GB
6 TB 500 GB
Development
10 GB
6 TB 500 GB
Test
10 GB
6 TB 500 GB
Development
10 GB
6 TB 500 GB
Test
10 GB
Total
45,57 TB
11. Team 1 Team 2 Team 3
6 TB 500 GB
Production
10 GB
600 GB 50 GB
Development
1 GB
600 GB 50 GB
Test
1 GB
600 GB 50 GB
Development
1 GB
600 GB 50 GB
Test
1 GB
600 GB 50 GB
Development
1 GB
600 GB 50 GB
Test
1 GB
Total
10.4 TB
10 % Subset 10 % Subset 10 % Subset
14. Minimize data usage
Save on hardware & infra
Reduce throughput times
Efficient data management
Protect customer information
Comply with regislation
Prevent brand damage
Maintain competitive advantages
Subsetting Anonymizing
Advantages of subsetting data Advantages of scrambling & masking data
20. Data model classification
Subset – Process data
Example: Customers, Orders, Contracts, Invoices, Transactions
Full – Master data
Example: Application data, configuration, master tables
Embty – Logging, non relevant history
Example: Logging tables, temp tabellen
Determine data to be subsetted
21.
22. Chain of systems
Method for deriving consistent subsets from multiple systems
Production Test/Development
Start Filter
All customers from The
Netherlands
Start Filter
All orders from customers in
the previous subset.
25. - Bank account balance
- Dept
- Medication
- Illness
- Religion
- Political preference
- Salary
- Phone history
- Et cetera…
- Name
- Date of birth
- Email
- Bank account number
- Social security number
- Adress
- Insurance number
- Cellphone number
- Et cetera..
Personal data
Identifying Characteristics
“Any information relating to an identified or identifiable natural person ("data subject")
Source: Data Protection Directive - Directive 95/46/EC
27. Shuffle
Shuffle values within same column
Conditional
Manipulate specified rows+
First name Last name Type
John
Max
Joe
Clark
Smith
Williams
DATPROF
Customer
Customer
Customer
Company
28. 321
First name Last name Type Comment E-Mail
John
Max
Joe
Smith
Williams
Clark
Blank
Delete values from columns
Scramble
Replace existing characters
j.clark@live.com
Smith_max@mail.com
i_am@JoeWilliams.de
“Brother of J. Clark”
“Has dept”
Customer
Customer
Customer
CompanyDATPROF
29. Nr. First name Last name Type Co.. E-mail Date of Birth
John
Max
Joe
Smith
Williams
Clark
DATPROF
123
Customer
Customer
Customer
Company
321
789
456
First day
Change dates to first day within same month and year
01-02-1954
01-11-1984
01-03-1974
Postal code
Date of Birth 1st day of month 1st day of year
87% 3.7% 0.04%
Source: research anonimity by Prof. Dr. Latanya Sweeney (Harvard University)
x.xxxxx@xxxx...
Xxxxx_xxx@xx...
x_xx@XxxXxxx...
30. Nr. First name Last name Type .. E-mail Date of birth
123
321
789
01-02-1954
01-11-1984
01-03-1974
Look-up
Replace values with values from a lookup table
James
Adrian
Thomas
John
Max
Joe
First names
Chris
Thomas
James
Ruben
Adrian
Michael
David
Reference data
Smith
Williams
Clark
DATPROF
Customer
Customer
Customer
Company
x.xxxxx@xxxx...
Xxxxx_xxx@xx...
x_xx@XxxXxxx...
31. Nr. First name Last name Type Comment E-mail Date of birth
Thomas
James
Adrian
Smith
Williams
Clark
DATPROF
123
Customer
Customer
Customer
Company
321
789
456
01-02-1954
01-11-1984
01-03-1974
Expression
Use custom made functions
Scrambled T.Smith@datprof.com
J.Willams@datprof.com
A.Clark@datprof.com
Scrambled
Scrambled
Doordat het team zelf bepaald hoeveel werk zij van de backlog aankunnen en daarvoor commitment afgeven. Plus het feit dat na de sprint de rest van de organisatie zien wat hun voortgang is, zorgt voor een onzettend gemotiveerd en effectief team.
Het bouwen van software is ontzettend veranderlijk. Gebruikers weten vaak niet precies wat ze willen totdat ze het voor hun zien of ermee kunnen werken. Daarvoor is prototype ontwikkeling en de mogelijk om na een sprint bij te sturen onzettend belangrijk.
Zeggen Scrum te doen, maar niet doen…….. Uitleggen welke fouten