This document discusses analyzing geospatial data with IBM Cloud Data Services and Esri ArcGIS. It provides an overview of using Cloudant as a NoSQL database to store geospatial data in GeoJSON format and then load it into IBM dashDB for analytics. GeoJSON data can be stored in Cloudant in three different formats - as simple geometry, feature collections, or features - and Cloudant provides APIs for geospatial queries, indexing, and replication of the data.
John Park, Offering Manager, for IBM Cloud Data Services covers the touchstones for tomorrow’s information systems: data and integration. Stovepipe applications are no longer acceptable, and siloed data sources must evolve and open up to the full enterprise. All this in an environment where more is expected faster, and at a lower cost. If your GIS doesn’t watch out, it will be replaced by less capable alternatives that “fit better” into mainstream IT. But dashDB, a cloud-native offspring of DB2, can provide a bridge that keeps both sides happy. This session introduce this popular cloud data warehousing solution and illustrate how it works in concert with ArcGIS. You will learn about the built-in geospatial functions in dashDB and how you can easily use them to build applications rapidly. You’ll see an application that uses weather data and mobile application data to calculate insurance risk, detect potential fraud, and prevent damage.
dashDB Enterprise MPP is a new fully managed cloud data warehouse service with massive scale and performance. Powered by IBM's network cluster architecture, dashDB MPP is an easy to use, self service solution for building: standalone data warehouses; data science data marts; hybrid warehousing; development and QA environments; and analytics for NoSQL. It is available through IBM Bluemix along with IBM's other Cloud Data Services, including Cloudant and SQL DB.
All your database are belong to us - Koop, Cloudant, Feature ServicesRaj Singh
Wouldn’t it be cool if every database could look like a FeatureService? Well that’s the promise of Koop (https://koopjs.github.io/), an open source effort to provide a standard REST API for web-based sources of vector geodata such as ArcGIS Online, Socrate, GitHub and Gist. Koop was started within Esri, but has a wide and varied community of contributors. This talk is about IBM’s work to develop a Koop “provider” for Cloudant, a JSON NoSQL document store.
IBM® dashDB™ is a fast, fully managed, cloud data warehouse that utilizes integrated analytics to rapidly deliver answers. dashDB’s unique in-database analytics, R predictive modeling and business intelligence tools free you to analyze your data and get precise insights, quicker. dashDB is simple to get up and running with rapid provisioning in IBM Bluemix™. You can test the solution or start using dashDB for no charge, for up to one gigabyte of data and then just $50 US
per month for 20 gigabytes of data storage. Larger instance sizes with multi-terabyte capacity are available as you grow your data, and as your users require a dedicated environment. Massively Parallel Processing (MPP) enables even faster query speeds as well as larger scale data sets.
IBM THINK 2019 - What? I Don't Need a Database to Do All That with SQL?Torsten Steinbach
You don't necessarily have to set up a relational database, tables and load data in order to use a surprisingly rich set of SQL capabilities on your data in the cloud. IBM SQL Query lets you analyze terabytes of distributed data of heterogeneous formats with a complete ANSI SQL dialect in a completely serverless usage model, elegantly ETL data between formats and partitioning layouts as needed, and run complex time series transformations, analysis and correlations with advanced built-in timeseries SQL algorithms that are differentiating in the entire industry. It also support a complete PostGIS compliant geospatial SQL function set. Come explore the stunningly advanced world of SQL without a database in IBM Cloud.
John Park, Offering Manager, for IBM Cloud Data Services covers the touchstones for tomorrow’s information systems: data and integration. Stovepipe applications are no longer acceptable, and siloed data sources must evolve and open up to the full enterprise. All this in an environment where more is expected faster, and at a lower cost. If your GIS doesn’t watch out, it will be replaced by less capable alternatives that “fit better” into mainstream IT. But dashDB, a cloud-native offspring of DB2, can provide a bridge that keeps both sides happy. This session introduce this popular cloud data warehousing solution and illustrate how it works in concert with ArcGIS. You will learn about the built-in geospatial functions in dashDB and how you can easily use them to build applications rapidly. You’ll see an application that uses weather data and mobile application data to calculate insurance risk, detect potential fraud, and prevent damage.
dashDB Enterprise MPP is a new fully managed cloud data warehouse service with massive scale and performance. Powered by IBM's network cluster architecture, dashDB MPP is an easy to use, self service solution for building: standalone data warehouses; data science data marts; hybrid warehousing; development and QA environments; and analytics for NoSQL. It is available through IBM Bluemix along with IBM's other Cloud Data Services, including Cloudant and SQL DB.
All your database are belong to us - Koop, Cloudant, Feature ServicesRaj Singh
Wouldn’t it be cool if every database could look like a FeatureService? Well that’s the promise of Koop (https://koopjs.github.io/), an open source effort to provide a standard REST API for web-based sources of vector geodata such as ArcGIS Online, Socrate, GitHub and Gist. Koop was started within Esri, but has a wide and varied community of contributors. This talk is about IBM’s work to develop a Koop “provider” for Cloudant, a JSON NoSQL document store.
IBM® dashDB™ is a fast, fully managed, cloud data warehouse that utilizes integrated analytics to rapidly deliver answers. dashDB’s unique in-database analytics, R predictive modeling and business intelligence tools free you to analyze your data and get precise insights, quicker. dashDB is simple to get up and running with rapid provisioning in IBM Bluemix™. You can test the solution or start using dashDB for no charge, for up to one gigabyte of data and then just $50 US
per month for 20 gigabytes of data storage. Larger instance sizes with multi-terabyte capacity are available as you grow your data, and as your users require a dedicated environment. Massively Parallel Processing (MPP) enables even faster query speeds as well as larger scale data sets.
IBM THINK 2019 - What? I Don't Need a Database to Do All That with SQL?Torsten Steinbach
You don't necessarily have to set up a relational database, tables and load data in order to use a surprisingly rich set of SQL capabilities on your data in the cloud. IBM SQL Query lets you analyze terabytes of distributed data of heterogeneous formats with a complete ANSI SQL dialect in a completely serverless usage model, elegantly ETL data between formats and partitioning layouts as needed, and run complex time series transformations, analysis and correlations with advanced built-in timeseries SQL algorithms that are differentiating in the entire industry. It also support a complete PostGIS compliant geospatial SQL function set. Come explore the stunningly advanced world of SQL without a database in IBM Cloud.
New! Real-Time Data Replication to SnowflakePrecisely
Your business is adopting the Snowflake cloud data platform to rapidly deliver data insights and lower the costs of your data warehouse. But you have a problem – what happens when data changes on your mainframe and IBM i systems? How do you make sure Snowflake is always up-to-date and in sync with these systems of record?
If you can’t integrate changes occurring on your mainframe and IBM i systems to Snowflake, your business will miss the critical data it needs to drive real-time insights and decision making.
Join us to learn how the latest enhancements to Precisely Connect help your business meet its data-driven goals by sharing changes made on legacy, mainframe, and IBM systems to Snowflake in real time.
During this webinar, you will learn more about:
- How to easily support data replication from mainframe and IBM i to Snowflake
- Connect’s enhanced data replication capabilities for cloud data platforms
- How customers are using Connect to support their cloud data platform strategies
Our March 2, 2016 event featured Billy Beane, Executive Vice President of Baseball Operations at the Oakland As and Derek Schoettle, GM of Analytics Platform Services at IBM. Billy and Derek shared their experiences of how professional sports teams and businesses alike are gaining hidden insights and competitive advantages by using the latest data discovery techniques and platforms.
View the webinar here - https://bit.ly/2ErkxYY
Enterprises are moving their data warehouse to the cloud to take advantage of reduced operational and administrative overheads, improved business agility, and unmatched simplicity.
The Impetus Workload Transformation Solution makes the journey to the cloud easier by automating the DW migration to cloud-native data warehouse platforms like Snowflake. The solution enables enterprises to automate conversion of source DDL, DML scripts, business logic, and procedural constructs. Enterprises can preserve their existing investments, eliminate error-prone, slow, and expensive manual practices, mitigate any risk, and accelerate time-to-market with the solution.
Join our upcoming webinar where Impetus experts will detail:
Cloud migration strategy
Critical considerations for moving to the cloud
Nuances of migration journey to Snowflake
Demo – Automated workload transformation to Snowflake.
To view - visit https://bit.ly/2ErkxYY
How Element 84 Raises the Bar on Streaming Satellite DataAmazon Web Services
GOES-16 is a source of critical data for monitoring smoke, flooding impacts, burn scars, volcanic ash, and weather. However, finding and using this data can require significant investment. Element 84 married video compression and streaming technology with NASA’s Cumulus data processing pipeline, plus AWS Managed Services, to make the entire GOES-16 archive interactive on an array of formats. Users can now easily identify dates of interest for events like natural disasters, and stage a subset of the archive for analysis. And all of this scales down to $0 when not in use.
Customer experience at disney+ through data perspectiveMartin Zapletal
Disney+ has rapidly scaled to provide a personalized and seamless experience to tens of millions of customers. This experience is powered by a robust data platform that ingests, processes and surfaces billions of events per hour using Delta lake, Databricks, and AWS technologies. The data produced by the platform is used by multitude of services including a recommendation engine for personalized experience, optimizing watch experience including group watch, and fraud and abuse prevention. In this session, you will learn how Disney+ built these capabilities, the architecture, technologies, design principles, and technical details that make it possible.
Introduce the Big-Data data characteristic, big-data process flow/architecture, and take out an example about EKG solution to explain why we are run into big data issue, and try to build up a big-data server farm architecture. From there, you can have more concrete point of view, what the big-data is.
NoSQL and Spatial Database Capabilities using PostgreSQLEDB
PostgreSQL is an object-relational database system. NoSQL on the other hand is a non-relational database and is document-oriented. Learn how the PostgreSQL database gives one the flexible options to combine NoSQL workloads with the relational query power by offering JSON data types. With PostgreSQL, new capabilities can be developed and plugged into the database as required.
Attend this webinar to learn:
- The new features and capabilities in PostgreSQL for new workloads, requiring greater flexibility in the data model
- NoSQL with JSON, Hstore and its performance and features for enterprises
- Spatial SQL - advanced features in PostGIS application with PostGIS extension
Vivint Smart Home's journey with Snowflake and migrating from SQL Server. We describe how we have setup snowflake from a people, process, and technology perspective.
From the Data Work Out event:
Performant and scalable Data Science with Dataiku DSS and Snowflake
Managing the whole process of setting up a machine learning environment from end-to-end becomes significantly easier when using cloud-based technologies. The ability to provision infrastructure on demand (IaaS) solves the problem of manually requesting virtual machines. It also provides immediate access to compute resources whenever they are needed. But that still leaves the administrative overhead of managing the ML software and the platform to store and manage the data.
A fully managed end-to-end machine learning platform like Dataiku Data Science Studio (DSS) that enables data scientists, machine learning experts, and even business users to quickly build, train and host machine learning models at scale, needs to access data from many different sources and can also access data provided by Snowflake. Storing data in Snowflake has three significant advantages: a single source of truth, shorten the data preparation cycle, scale as you go.
Smartsheet’s Transition to Snowflake and Databricks: The Why and Immediate Im...Databricks
Join this session to hear why Smartsheet decided to transition from their entirely SQL-based system to Snowflake and Databricks, and learn how that transition has made an immediate impact on their team, company and customer experience through enabling faster, informed data decisions.
“Liberté, Égalité, Fraternité” (Liberty, Equality, Fraternity), is the slogan of France, coined around the time of the French Revolution. It also seems a pretty appropriate slogan for the mini revolution that is happening right now with CICS and WebSphere. The Liberty profile is a highly composable and dynamic application server runtime environment that is shipped as a part of both WebSphere and CICS. This session will introduce Liberty in CICS, compare the capability with WebSphere (note the ‘equality’ word) and discuss how these new Liberty applications can interact with and support the established fraternity of existing CICS applications that run your core business.
Integrating Structure and Analytics with Unstructured DataDATAVERSITY
How can you make sense of messy data? How do you wrap structure around non-relational, flexibly structured data? With the growth in cloud technologies, how do you balance the need for flexibility and scale with the need for structure and analytics? Join us for an overview of the marketplace today and a review of the tools needed to get the job done.
During this hour, we'll cover:
- How big data is challenging the limits of traditional data management tools
- How to recognize when tools like MongoDB, Hadoop, IBM Cloudant, R Studio, IBM dashDB, CouchDB, and others are the right tools for the job.
New! Real-Time Data Replication to SnowflakePrecisely
Your business is adopting the Snowflake cloud data platform to rapidly deliver data insights and lower the costs of your data warehouse. But you have a problem – what happens when data changes on your mainframe and IBM i systems? How do you make sure Snowflake is always up-to-date and in sync with these systems of record?
If you can’t integrate changes occurring on your mainframe and IBM i systems to Snowflake, your business will miss the critical data it needs to drive real-time insights and decision making.
Join us to learn how the latest enhancements to Precisely Connect help your business meet its data-driven goals by sharing changes made on legacy, mainframe, and IBM systems to Snowflake in real time.
During this webinar, you will learn more about:
- How to easily support data replication from mainframe and IBM i to Snowflake
- Connect’s enhanced data replication capabilities for cloud data platforms
- How customers are using Connect to support their cloud data platform strategies
Our March 2, 2016 event featured Billy Beane, Executive Vice President of Baseball Operations at the Oakland As and Derek Schoettle, GM of Analytics Platform Services at IBM. Billy and Derek shared their experiences of how professional sports teams and businesses alike are gaining hidden insights and competitive advantages by using the latest data discovery techniques and platforms.
View the webinar here - https://bit.ly/2ErkxYY
Enterprises are moving their data warehouse to the cloud to take advantage of reduced operational and administrative overheads, improved business agility, and unmatched simplicity.
The Impetus Workload Transformation Solution makes the journey to the cloud easier by automating the DW migration to cloud-native data warehouse platforms like Snowflake. The solution enables enterprises to automate conversion of source DDL, DML scripts, business logic, and procedural constructs. Enterprises can preserve their existing investments, eliminate error-prone, slow, and expensive manual practices, mitigate any risk, and accelerate time-to-market with the solution.
Join our upcoming webinar where Impetus experts will detail:
Cloud migration strategy
Critical considerations for moving to the cloud
Nuances of migration journey to Snowflake
Demo – Automated workload transformation to Snowflake.
To view - visit https://bit.ly/2ErkxYY
How Element 84 Raises the Bar on Streaming Satellite DataAmazon Web Services
GOES-16 is a source of critical data for monitoring smoke, flooding impacts, burn scars, volcanic ash, and weather. However, finding and using this data can require significant investment. Element 84 married video compression and streaming technology with NASA’s Cumulus data processing pipeline, plus AWS Managed Services, to make the entire GOES-16 archive interactive on an array of formats. Users can now easily identify dates of interest for events like natural disasters, and stage a subset of the archive for analysis. And all of this scales down to $0 when not in use.
Customer experience at disney+ through data perspectiveMartin Zapletal
Disney+ has rapidly scaled to provide a personalized and seamless experience to tens of millions of customers. This experience is powered by a robust data platform that ingests, processes and surfaces billions of events per hour using Delta lake, Databricks, and AWS technologies. The data produced by the platform is used by multitude of services including a recommendation engine for personalized experience, optimizing watch experience including group watch, and fraud and abuse prevention. In this session, you will learn how Disney+ built these capabilities, the architecture, technologies, design principles, and technical details that make it possible.
Introduce the Big-Data data characteristic, big-data process flow/architecture, and take out an example about EKG solution to explain why we are run into big data issue, and try to build up a big-data server farm architecture. From there, you can have more concrete point of view, what the big-data is.
NoSQL and Spatial Database Capabilities using PostgreSQLEDB
PostgreSQL is an object-relational database system. NoSQL on the other hand is a non-relational database and is document-oriented. Learn how the PostgreSQL database gives one the flexible options to combine NoSQL workloads with the relational query power by offering JSON data types. With PostgreSQL, new capabilities can be developed and plugged into the database as required.
Attend this webinar to learn:
- The new features and capabilities in PostgreSQL for new workloads, requiring greater flexibility in the data model
- NoSQL with JSON, Hstore and its performance and features for enterprises
- Spatial SQL - advanced features in PostGIS application with PostGIS extension
Vivint Smart Home's journey with Snowflake and migrating from SQL Server. We describe how we have setup snowflake from a people, process, and technology perspective.
From the Data Work Out event:
Performant and scalable Data Science with Dataiku DSS and Snowflake
Managing the whole process of setting up a machine learning environment from end-to-end becomes significantly easier when using cloud-based technologies. The ability to provision infrastructure on demand (IaaS) solves the problem of manually requesting virtual machines. It also provides immediate access to compute resources whenever they are needed. But that still leaves the administrative overhead of managing the ML software and the platform to store and manage the data.
A fully managed end-to-end machine learning platform like Dataiku Data Science Studio (DSS) that enables data scientists, machine learning experts, and even business users to quickly build, train and host machine learning models at scale, needs to access data from many different sources and can also access data provided by Snowflake. Storing data in Snowflake has three significant advantages: a single source of truth, shorten the data preparation cycle, scale as you go.
Smartsheet’s Transition to Snowflake and Databricks: The Why and Immediate Im...Databricks
Join this session to hear why Smartsheet decided to transition from their entirely SQL-based system to Snowflake and Databricks, and learn how that transition has made an immediate impact on their team, company and customer experience through enabling faster, informed data decisions.
“Liberté, Égalité, Fraternité” (Liberty, Equality, Fraternity), is the slogan of France, coined around the time of the French Revolution. It also seems a pretty appropriate slogan for the mini revolution that is happening right now with CICS and WebSphere. The Liberty profile is a highly composable and dynamic application server runtime environment that is shipped as a part of both WebSphere and CICS. This session will introduce Liberty in CICS, compare the capability with WebSphere (note the ‘equality’ word) and discuss how these new Liberty applications can interact with and support the established fraternity of existing CICS applications that run your core business.
Integrating Structure and Analytics with Unstructured DataDATAVERSITY
How can you make sense of messy data? How do you wrap structure around non-relational, flexibly structured data? With the growth in cloud technologies, how do you balance the need for flexibility and scale with the need for structure and analytics? Join us for an overview of the marketplace today and a review of the tools needed to get the job done.
During this hour, we'll cover:
- How big data is challenging the limits of traditional data management tools
- How to recognize when tools like MongoDB, Hadoop, IBM Cloudant, R Studio, IBM dashDB, CouchDB, and others are the right tools for the job.
Spark working with a Cloud IDE: Notebook/Shiny AppsData Con LA
Abstract:-
The Problem: Energy inefficiency within public/private buildings in the City of New York.
The Goal: Take meter(Sensor) data, solve the inefficiencies through better insights.
The Solution: Visualization and Reporting through the Shiny App to gain knowledge in past, and present usage patterns. In addition to those patterns, compare and gain insights/predictions on energy usage.
Spark's Dataframes and RDD's will be used in concert with panda (library) to clean and model/prepare data for the R Shiny App. The message to convey in this meetup discussion is to show the capabilities of Spark while using DSX and RStudio/Shiny App to create visualization/reporting that will be able to give insights to the end user.
There are a few techniques that we will present in this notebook with both modeling and ML: Linear Regression, K-Means clustering for identifying inefficient buildings, (Statistical) Classification Modeling, followed by a confusion matrix (error matrices).
Bio:-
Thomas Liakos has been an Open Source Systems Engineer for 11 years and he has 8 years of experience in Cloud and hybrid environments. Prior to IBM Thomas was at Gem.co: Sr. Systems Architect. and CrowdStrike: DevOps / Systems Engineer - Cloud Operations. Thomas has expertise in Spark, Python, Systems and Configuration Management, Architecture, Data Warehousing, and Data Engineering.
Ingesting Data at Blazing Speed Using Apache OrcDataWorks Summit
Big SQL is a SQL engine for Hadoop that excels at performance and scalability at high concurrency. Big SQL complements and integrates with Apache Hive for both data and metadata. An architecture that separates compute from storage allows Big SQL to support multiple open data formats natively. Until recently, Parquet provided a significant performance advantage over other data formats for SQL on Hadoop. The landscape changed when ORC became a top level Apache project independent from Hive. Gone were the days of reading ORC files using slow, single-row-at-a-time Hive Serdes. The new vectorized APIs in the Apache ORC libraries make it possible to ingest ORC data at blazing speed. This talk is about the journey leading to ORC taking the crown of best performing data format for Big SQL away from Parquet. We'll have a look under the hood at the architecture of Big SQL ORC readers, and how to tune them. We'll share lessons learned in walking the fine line between maximizing performance at scale and avoiding dreaded Java OOMs . You'll learn the techniques that SQL engines use for fast data ingestion, so that you can leverage the full potential of Apache ORC in any application.
Speaker:
Gustavo Arocena, Big Data Architect, IBM
Tip from ConnectED: Notes Goes Cloud: The IBM Notes Browser Plug-in Integrate...SocialBiz UserGroup
At IBM ConnectED last January, speaker Martin Garrels, from GAD eG, presented how GAD and IBM created an innovative solution enabling the IBM Notes Browser Plug-in to work in a fully integrated browser-based workplace. GAD is moving its workplace to a web-based cloud solution, using the power of iNotes, XPages, Connections, WebSphere Portal and the IBM Notes Browser Plug-in. With an IBM Domino infrastructure of about 1900 servers and 65,000 users in a multi-domain environment, GAD serves about 10,000 custom applications. Many applications are web-enabled with XPages technology, but a lot more are legacy applications, which are still in use. To put them in a browser context, the GAD and IBM team overcame many challenges.
For more information, go to the SocialBiz User Group at https://reg.socialbizug.org/
IBM Connect 2016 - Logging Wars: A Cross Product Tech Clash Between Experts -...Chris Miller
Things WILL get VERY technical when two experts face-off in a unique session that explores polar perceptions regarding various types of logs, verbosity levels, data extraction, responses for alerts, and more. Be it Domino, Sametime, or Traveler operating on-prem. or in Hybrid and Cloud environments, it is vital to have an understanding of log data structure, what is (or isn't) logged and why, and how to search logs effectively. But aren't there ways to find your information without having to pipe everything into the log? Where does one's best practice end and another's begin? From this collision of opposing viewpoints and real-world stories, you'll take away knowledge and tools ready to deploy to various scenarios, products, and log types.
Session 2546 - Solving Performance Problems in CICS using CICS Performance A...nick_garrod
InterConnect Session 2546, Solving Performance Problems in CICS using CICS Performance Analyzer. CICS performing well is critical to your Enterprise. Knowing how to solve performance problems is just as critical. This session will concentrate on the most common performance problems seen in the Level 2 Service area. Monitoring and Statistic data will be used to show what to look for and how to avoid these common problems. CICS Performance Analyzer will be used as the primary tool to format and present the data needed to solve these performance issues.
SHARE2016: DevOps - IIB Administration for Continuous Delivery and DevOpsRob Convery
Are you new to IBM Integration Bus? Do you want to know how to configure, administer and monitor your nodes? Do you want to make it easier on yourself when deploying your message flow applications across multiple servers? Would you like to keep a record of all of the messages which flow through your applications? Would you like to know how you can configure a Continuous Integration and Deployment pipeline for you IIB integrations? If so come along and find out about how to administer and monitor your IBM Integration Bus environment.
The presentation will first cover the basics of administering and monitoring your Integration Nodes. Looking at the available commands and their options, as well as the most recent V10 improvements, including enhancements to the product runtime, covering the extended webui, policy, Integration Toolkit, command line, and programmatic front-ends.
Using the basics learnt initially, this session will then take a look at how you build a Continuous Integration pipeline using technologies such as git, Ant & Jenkins to programmatically configure your Nodes, create, build and test your integrations, and then deploy them to production.
A description of what REST is and is not useful for followed by a walkthrough of how to use REST API's to access Informix databases. Includes new features released for Informix 12.10xC7
DESY's new data taking and analysis infrastructure for PETRA IIIUlf Troppens
DESY (Deutsches Elektronen-Synchrotron) implemented a new IT architecture for the data taking and data analysis of measured data of the PETRA III particle accelerator. The new system needs to handle more than 20 gigabyte per second at peak performance in order to enable scientists worldwide to gain faster insights into the atomic structure of novel semiconductors, catalysts, biological cells and other samples. The implemented solution transfers to other fields of data centric science where remote devices (e.g. sensors, cameras) generate huge amounts of data which needs to be analyzed in a central data center. The solution is based on IBM Spectrum Scale and IBM Elastic Storage Server.
The system is the result of a 1-year collaboration between DESY and IBM. I am honored and proud to be member of the project team.
http://www.desy.de/infos__services/presse/pressemeldungen/@@news-view?id=8741
https://www-03.ibm.com/press/us/en/pressrelease/44587.wss
Similar to Analyzing GeoSpatial data with IBM Cloud Data Services & Esri ArcGIS (20)
Since GeoJSON is a standard for storing geographic data in JSON format, it is a best practice to adhere to this format when storing geo-coordinates in Cloudant and CouchDB.
The concept of data movement lies at the heart of Apache CouchDB. CouchDB’s replication protocol lets developers synchronize copies of their data to remote CouchDB-based systems – including Cloudant – at the push of a button. Replication jobs can also run continuously, and in both directions.
Mango allows users to declaratively define and query Apache CouchDB indexes. Mango leverages Lucene not only to perform text search, but also to enable ad-hoc querying capabilities.
CouchDB is a document database. It stores JSON objects with a few special field names. The _id field represents a unique identifier for a document. The _rev field is the revision marker for a document. The _rev field is used for Multi-Version Concurrency Control, a form of optimistic concurrency.
Apache CouchDB is accessed through an HTTP API. HTTP Basic authentication is a simple way to authenticate with an HTTP server. Other approaches, such as cookies and OAuth, are often used as well.
For more than 10 years, developers have relied on Apache(R) CouchDB(TM) - a versatile and highly scalable open source database - to build apps for web, mobile and IoT platforms.
The release of CouchDB 2.0 in 2016 has generated even more interest in the freely available JSON database, which now includes clustering capabilities contributed from IBM Cloudant for high availability and performance.
In the world of NoSQL, each database has its own strengths and weaknesses. Understanding which open source database is "the right tool for the job" is half the battle if you want to start building better applications quickly. IBM developer advocate Glynn Bird explores practical examples of how two popular NoSQL databases - the Cloudant JSON document store and the Redis in-memory key-value store - can be used together to create performant and scalable Web applications. It also includes real world use cases you can try today, for free, using the IBM Cloud Data Services suite of fully managed NoSQL databases-as-a-service.
IBM Cloudant describe the geospatial tools used in their database-as-a-service offering (DBaaS). Based upon Apache CouchDB, the geospatial extensions used by IBM Cloudant rely on a number of well known open source libraries to provide geospatial indexing, query and projection support to Apache CouchDB. Discussion topics include:
- Overview of the architecture & tools
- Best practices for building geospatial apps with NoSQL doc stores
- Use cases for leveraging geospatial capabilities of a NoSQL doc store
BM Cloudant is a NoSQL Database-as-a-Service. Discover how you can outsource the data layer of your mobile or web application to Cloudant to provide high availability, scalability and tools to take you to the next level.
SQL-based databases have been around for decades and they power a wide range of applications. So what exactly do NoSQL databases bring to the table? In this webcast, you'll find out how NoSQL can liberate your development cycle, allow your application to scale and improve your system's uptime.
Find out how NoSQL can help your application with practical examples and use-cases from our Cloud Data Services Developer Advocate Glynn Bird. This webinar won't dwell on the science behind the database, but will walk you through real-life use-cases for NoSQL technologies that you can start using today.
Webinar: https://youtu.be/M_Jqw
Learn what you need to consider when moving from the world of relational databases to a NoSQL document store.
Hear from Developer Advocate Glynn Bird as he explains the key differences between relational databases and JSON document stores like Cloudant, as well as how to dodge the pitfalls of migrating from a relational database to NoSQL.
Presented by David Taieb, Architect, IBM Cloud Data Services
Along with Spark Streaming, Spark SQL and GraphX, MLLib is one of the four key architectural components of Spark. It provides easy-to-use (even for beginners), powerful Machine Learning APIs that are designed to work in parallel using Spark RDDs. In this session, we’ll introduce the different algorithms available in MLLib, e.g. supervised learning with classification (binary and multi class) and regression but also unsupervised learning with clustering (K-means) and recommendation systems. We’ll conclude the presentation with a deep dive on a sample machine learning application built with Spark MLLib that predicts whether a scheduled flight will be delayed or not. This application trains a model using data from real flight information. The labeled flight data is combined with weather data from the “Insight for Weather” service available on IBM Bluemix Cloud Platform to form the training, test and blind data. Even if you are not a black belt in machine learning, you will learn in this session how to leverage powerful Machine Learning algorithms available in Spark to build interesting predictive and prescriptive applications.
About the Speaker: For the last 4 years, David has been the lead architect for the Watson Core UI & Tooling team based in Littleton, Massachusetts. During that time, he led the design and development of a Unified Tooling Platform to support all the Watson Tools including accuracy analysis, test experiments, corpus ingestion, and training data generation. Before that, he was the lead architect for the Domino Server OSGi team responsible for integrating the eXpeditor J2EE Web Container in Domino and building first class APIs for the developer community. He started with IBM in 1996, working on various globalization technologies and products including Domino Global Workbench (used to develop multilingual Notes/Domino NSF applications) and a multilingual Content Management system for the Websphere Application Server. David enjoys sharing his experience by speaking at conferences. You’ll find him at various events like the Unicode conference, Eclipsecon, and Lotusphere. He’s also passionate about building tools that help improve developer productivity and overall experience.
Mobile web apps shouldn't stop working when there's no network connection. Offline-enabled apps built using PouchDB can provide a better, faster user experience while potentially reducing battery and bandwidth usage.
Hear from Developer Advocate Glynn Bird to find out how to use the HTML5 Offline Application Cache, PouchDB, IBM Cloudant and Cordova/PhoneGap to develop fully-featured and cross-platform native apps and responsive mobile web apps that work just as well offline as they do online.
Cloud and Software as a Service (SaaS) can make a huge impact on a business. Unfortunately, most start the evaluation of SaaS from an IT perspective and traditional data center advantages (i.e. on-premises costs, staffing and savings). While savings are important, cloud is about agility and speed. For these reasons, line-of-business (LOB) leaders have been more interested in SaaS solutions. Learn how Cognos Business Intelligence on Cloud and IBM dashdb make it simple to get started with collaboration, reporting and analytics.
Many Oracle pros are looking to take their data warehousing strategy to the cloud, but have been waiting for a cloud solution that offers both compatibility and ease of use. Well, the wait is over - with IBM dashDB, you can leverage your existing Oracle (as well as SQL) application skills, and get all the cost, scalability and performance advantages of a fully managed data warehousing service in the IBM Cloud.
Learn about IBM's Hadoop offering called BigInsights. We will look at the new features in version 4 (including a discussion on the Open Data Platform), review a couple of customer examples, talk about the overall offering and differentiators, and then provide a brief demonstration on how to get started quickly by creating a new cloud instance, uploading data, and generating a visualization using the built-in spreadsheet tooling called BigSheets.
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/
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...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.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
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.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.