VMWare vFabric SQLFire - scalable SQL instead of NoSQL
There is quite a bit of buzz thesedays on "NoSQL" databases. The lack of transactions and good support for querying (SQL) has been a problem for many to adopt these solutions. This talk presents, VMWare SQLFire, a distributed SQL data management solution that melds Apache Derby (borrowing SQL drivers, parsing and some aspects of the engine) and an object data grid (GemFire) to offer a horizontally scalable, memory oriented data management system where developers can continue to use SQL. We focus on new primitives that extend the well known SQL Data definition syntax for data partitioning and replication strategies but leaving the "select" and data manipulation part of SQL intact so it only minimally impacts your application.
I gave this presentation at What's next, Paris 2011(http://www.whatsnextparis.com/abouttheseminar.html).
VMWare vFabric SQLFire - scalable SQL instead of NoSQL
There is quite a bit of buzz thesedays on "NoSQL" databases. The lack of transactions and good support for querying (SQL) has been a problem for many to adopt these solutions. This talk presents, VMWare SQLFire, a distributed SQL data management solution that melds Apache Derby (borrowing SQL drivers, parsing and some aspects of the engine) and an object data grid (GemFire) to offer a horizontally scalable, memory oriented data management system where developers can continue to use SQL. We focus on new primitives that extend the well known SQL Data definition syntax for data partitioning and replication strategies but leaving the "select" and data manipulation part of SQL intact so it only minimally impacts your application.
I gave this presentation at What's next, Paris 2011(http://www.whatsnextparis.com/abouttheseminar.html).
Fastest way to revise for the a business analyst interview. A compact yet comprehensive guide to SQL commands, Joins, examples, syntax, data types and lot more...
From Prototype to Production: A Crash Course in HardwareHoyaMaxa
Hardware is hard. When I began my journey as a hardware entrepreneur, I quickly realized how hard, but also how inaccessible much of the knowledge was. This is the presentation that I wish had been around when I started. Covering the "internet of things", crowdfunding, sensors, Design for Manufacturing, Design for Assembly, Contract Manufacturers, and so much more!
Please contact me to use/borrow/license! Thanks!
Fastest way to revise for the a business analyst interview. A compact yet comprehensive guide to SQL commands, Joins, examples, syntax, data types and lot more...
From Prototype to Production: A Crash Course in HardwareHoyaMaxa
Hardware is hard. When I began my journey as a hardware entrepreneur, I quickly realized how hard, but also how inaccessible much of the knowledge was. This is the presentation that I wish had been around when I started. Covering the "internet of things", crowdfunding, sensors, Design for Manufacturing, Design for Assembly, Contract Manufacturers, and so much more!
Please contact me to use/borrow/license! Thanks!
Stefan & Irene photo with team at Cinnamon hotel Saigon. They send the Thank you letter to Cinnamon Hotel Saigon for their beautiful, enjoyable stay in December 2012. They appreciate the nice atmosphere, delicious breakfast, the organic attention to client . Also they enjoy the lovely rooms and especially the exceptional friendliness of Cinnamon Hotel team. Visitor at Cinnamon Hotel feel entirely welcome. They adore als the piece of craft art the team made to them. Stefan and Iren wish Cinnamon Hotel a Happy New Year 2013 and all the best for the team and their family of Cinnamon Hotel.
The RED Advisers is a multidisciplinary company that provides consulting services in various areas of real estate and tourism, formed by a group of highly qualified professionals.
Data Definition Language (DDL), Data Definition Language (DDL), Data Manipulation Language (DML) , Transaction Control Language (TCL) , Data Control Language (DCL) - , SQL Constraints
A classification of diseases may be defined as a system of categories to which
morbid entities are assigned according to established criteria. There are many
possible axes of classification and the one selected will depend upon the use to
be made of the statistics to be compiled. A statistical classification of diseases
must encompass the entire range of morbid conditions within a manageable
number of categories.
The 10th revision of the International statistical classification of diseases and
related health problems is the latest in a series that was formalized in 1893 as
the Bertillon classification or International list of causes of death. A complete
review of the historical background to the classification is given in Volume 2.
While the title has been amended to make clearer the content and purpose and
to reflect the progressive extension of the scope of the classification beyond
diseases and injuries, the familiar abbreviation ‘ICD’ has been retained. In the
updated classification, conditions have been grouped in a way that was felt to
be most suitable for general epidemiological purposes and the evaluation of
health care.
Work on the 10th revision of the ICD started in September 1983 when a
Preparatory Meeting on ICD-10 was convened in Geneva. The programme of
work was guided by regular meetings of heads of WHO collaborating centres
for classification of diseases. Policy guidance was provided by a number of
special meetings, including those of the expert committee on the International
classification of diseases – 10th revision, held in 1984 and 1987.
In addition to the technical contributions provided by many specialist groups
and individual experts, a large number of comments and suggestions were
received from WHO Member States and regional offices as a result of the
global circulation of draft proposals for revision in 1984 and 1986. From the
comments received, it was clear that many users wished the ICD to encompass
types of data other than the ‘diagnostic information’ (in the broadest sense of the
term) that it has always covered. In order to accommodate the perceived needs
of these users, the concept arose of a ‘family’ of classifications centred on the
traditional ICD with its familiar form and structure. The ICD itself would thus
meet the requirement for diagnostic information for general purposes, while a
variety of other classifications would be used in conjunction with it and would
deal either with different approaches to the same information or with different
information (notably medical and surgical procedures and disablement).
Following suggestions at the time of development of the ninth revision of
the classification that a different basic structure might better serve the needs
of the many and varied users, several alternative models were evaluated. It
became clear, however, that the traditional single-variable-axis design of
INTERNATIONAL CLASSIFICATION OF DISEASES
the classification, and other aspects of its structure th
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.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
8. Primary Keys What is a Primary Key: A Primary key is a field/attribute in a table which is used to uniquely identify a record Eg: Consider a dream database Here, a particular record can be uniquely located using the DreamNumber and hence, it is taken as the Primary key. If there are more than fields, eligible of being the primary key, the decision of choosing one among them lies with the DB designer
9. Primary Key Adding a Primary Key: A Table must have only one primary key. The Primary key must be defined during the creation of the table. Syntax: Create table <tableName> ( <fieldName1><field1Type> primary key, ..); Example: Consider the creation of the following table. The field ‘Dream Number’ is to be designated as the primary key Create table dreamtable( dreamnumberintprimary key, dream varchar(10), dreamdate date, dreamtime time, dreamtypevarchar(10)) ;
10. Redefining primary key Now, let us take a step back and redefine the primary key that we have learnt already. The definition that we learnt was: A Primary key is a field which lets us to uniquely identify a record in a table. This definition may sound intuitive, but in real word cases, a single field may not be enough to identify a record in a table. In such cases, a collection (two or more) of fields are used as a primary key. Consider the following example of a hospital’s patient table:
11. Redefining primary key In this case, it would be possible to locate a record uniquely only with information of more than one field values. Example: PatientID, Date of Admisssion and Time of Admission can be combined to form a primary key. The SQL Command to do this is via a constraint: create table <tableName> (<field names>,…, constraint <constraintName> primarykey(<filedName1>,<fieldName2>,..) ); Example: create table Patients(patientidvarchar(10), patientnamevarchar(20), dateofadmission date, timeofadmission time, issue varchar(20),constraint patientpkeysprimary key(patientid, dateofadmission, timeofadmission) );
12. Adding primary keys to existing tables The SQL Server allows primary keys to be added to an existing table. Syntax: ALTER TABLE <tableName> ADD CONSTRAINT <constraintName> PRIMARY KEY (<FieldName>); Example: Consider the patient database. The command to define the primary key after creating the table is: Alter table Patients add constraint patientpkeysprimary key(patientid, dateofadmission, timeofadmission) );
13. Foreign Keys Foreign Key: A Foreign key is a field/attribute in one table which is used as a primary key in another table Eg: Consider a dream database Every foreign key value must be present as a primary key in the referenced table. Eg: A dream number ‘3’ isn’t possible in ‘Luck Table’ unless such a dream number exists in the ‘Dream Table’ Dream Table Notice that foreign key entries can repeat (where-as primary key entries can’t!) Foreign Key Primary Key Luck Table Refer-ences
14. Foreign Keys In SQL Server, a foreign key is created as follows: Create table <Table2_Name> (<filedName1> foreign key references <Table1_Name> (Table1FieldName)); In the example that we just considered, the dreamNumberof the Luck Table is using the value of the primary Key dreamNumberfrom Dream Table. Hence, it is a foreign Key. The SQL statement to effect this is: Create table lucktable (dreamnumberintforeign key references dream(dreamnumber), luck varchar(15), predictor varchar(20)); NOTE: It is essential to create the table which is being referenced by the foreign key before creating the foreign key itself.
15. Adding foreign keys to existing tables The SQL Server allows foreign keys to be added to an existing table. Syntax: ALTER TABLE <tableName> ADD FOREIGN KEY (<fieldName>) REFERENCES <referencedTable>(<referencedFieldName>); Example: Table B has an attribute B1. B1 references to the primary key A1 of table A. Now, the command to add B1 as a foreign key of B is as follows: Table A Primary Key of A Table B Field A1 Foreign Key of B Field B1 << B1 references A1 Alter table B add foreign key(B1) references A(A1) ;
16. Not Null Constraint In feeding data into a database, it lies with the user to feed data for a field or assign a null value. But sometimes, the value of the field may be highly valuable for data processing. In such places, we may prevent a ‘null’ from being assigned to a field by using the not null constraint. Eg: Consider a customer table. Here, the name of the customer is very important. So, it can be made to be not null. Note: CutomerID being a primary key, inherently, can never be null. Create table customer(customeridint primary key, name varchar(10) not null, address varchar(30)); An attempt to insert a null value into a not-null field, will be flagged as an error.
17. Unique Constraint In SQL Server, it is possible to designate a field to be unique, .i.e., the field will not accept duplicate values. Primary keys are inherently unique in nature. Eg: Consider a customer table. Here, the credit card number of the customers will be unique. Create table customer(customeridint primary key, name varchar(10) not null, creditcardnumbervarchar(20) unique); An attempt to insert a credit card number that already exists in the table will be flagged as an error.
18. Check Constraint A Check constraint is used to specify some rules for the data that can be stored for a field. A Check constraint can be defined while creating a table (with create table) or can be added to an existing table. While adding a check constraint to an existing table, the data that the table holds is checked against the constraint being defined. To prevent this checking, the nocheck command can be used. A Check constraint can be defined on a single column(field) or across multiple columns of the same table. fieldname can take values between 1 and 100. eg: 1,2,3,…,99,100 SQL Syntax: Create table <tableName> (<fieldname> check (fieldname > 100) ); Create table <tableName> (<fieldname> check (fieldname between 1 and 100) ); Create table <tableName> (<fieldname> check (fieldname like ‘[0-9][0-9][a-z][A-Z]’) ); [0-9]: Denotes a single value in the range specified
19. Adding Check Constraint to an existing table It is possible to add check constraints to existing tables using the alter table command: Syntax: ALTER TABLE <tableName> ADD CHECK (<fieldName> <condition>); Example: ALTER TABLE student ADD CHECK (cgpa Between 0 and 10 );