A presentation from the Data Works Summit conference in 2017 that looks how Worldpay, a major payments provider, deployed a secure Hadoop cluster to support multiple business cases in a multi-tenancy cluster.
Big Data Week 2016 - Worldpay - Deploying Secure ClustersDavid Walker
A presentation from the Big Data Week conference in 2016 that looks how Worldpay, a major payments provider, deployed a secure Hadoop cluster in order to meet business requirements
Storage Characteristics Of Call Data Records In Column Store DatabasesDavid Walker
This document summarizes the storage characteristics of call data records (CDRs) in column store databases. It discusses what CDRs are, what a column store database is, and how efficient column stores are for storing CDR and similar machine-generated data. It provides details on the structure and content of sample CDR data, how the data was loaded into a Sybase IQ column store database for testing purposes, and the results in terms of storage characteristics and what would be needed for a production environment.
Openworld04 - Information Delivery - The Change In Data Management At Network...David Walker
Network Rail implemented a new information delivery strategy using Oracle technologies like the Balanced Scorecard, Discoverer, and Portal. They developed executive scorecards quickly for mandated KPIs and then additional scorecards. Data comes from various sources into staging areas and warehouses accessible with Discoverer. A portal provides integrated access. Applications replace Excel/Access and improve data quality. The approach involves a small agile team and spreading solutions across the business.
IOUG93 - Technical Architecture for the Data Warehouse - PresentationDavid Walker
The document outlines a technical architecture for implementing a data warehouse. It discusses business analysis, database schema design, project management, data acquisition, building a transaction repository, data aggregation, data marts, metadata and security, middleware and presentation layers. The goal is to help users find the information they need from the data warehouse. Contact information is provided at the end.
1. The document describes building an analytical platform for a retailer by using open source tools R and RStudio along with SAP Sybase IQ database.
2. Key aspects included setting up SAP Sybase IQ as a column-store database for storage and querying of data, implementing R and RStudio for statistical analysis, and automating running of statistical models on new data.
3. The solution provided a low-cost platform capable of rapid prototyping of analytical models and production use for predictive analytics.
Data warehousing change in a challenging environmentDavid Walker
This white paper discusses the challenges of managing changes in a data warehousing environment. It describes a typical data warehouse architecture with source systems feeding data into a data warehouse and then into data marts or cubes. It also outlines the common processes involved like development, operations and data quality processes. The paper then discusses two major challenges - configuration/change management as there are frequent changes from source systems, applications and technologies that impact the data warehouse. The other challenge is managing and improving data quality as issues from source systems are often replicated in the data warehouse.
The document discusses six governance processes for data and business intelligence: data lifecycle, data models, data quality, data security, data warehousing, and metadata. For each process, it provides an overview of why governance is important in that area, and what the governance process will do to manage issues and ensure requirements are met. The governance processes aim to balance various factors, control changes, and provide oversight and accountability for data management.
How Real TIme Data Changes the Data Warehousemark madsen
Surveys show a growing demand for more up-to-date data in our BI environments. To meet these needs requires changing from a strict reliance on nightly batch-style ETL to other methods. What is often ignored is how this affects the data warehouse. This shift introduces new technology and methods, which means the warehouse must support new types of workloads.
• Methods and tools for processing up-to-date data
• New requirements for your data warehouse database or platform
• What to look for as you address these requirements
Big Data Week 2016 - Worldpay - Deploying Secure ClustersDavid Walker
A presentation from the Big Data Week conference in 2016 that looks how Worldpay, a major payments provider, deployed a secure Hadoop cluster in order to meet business requirements
Storage Characteristics Of Call Data Records In Column Store DatabasesDavid Walker
This document summarizes the storage characteristics of call data records (CDRs) in column store databases. It discusses what CDRs are, what a column store database is, and how efficient column stores are for storing CDR and similar machine-generated data. It provides details on the structure and content of sample CDR data, how the data was loaded into a Sybase IQ column store database for testing purposes, and the results in terms of storage characteristics and what would be needed for a production environment.
Openworld04 - Information Delivery - The Change In Data Management At Network...David Walker
Network Rail implemented a new information delivery strategy using Oracle technologies like the Balanced Scorecard, Discoverer, and Portal. They developed executive scorecards quickly for mandated KPIs and then additional scorecards. Data comes from various sources into staging areas and warehouses accessible with Discoverer. A portal provides integrated access. Applications replace Excel/Access and improve data quality. The approach involves a small agile team and spreading solutions across the business.
IOUG93 - Technical Architecture for the Data Warehouse - PresentationDavid Walker
The document outlines a technical architecture for implementing a data warehouse. It discusses business analysis, database schema design, project management, data acquisition, building a transaction repository, data aggregation, data marts, metadata and security, middleware and presentation layers. The goal is to help users find the information they need from the data warehouse. Contact information is provided at the end.
1. The document describes building an analytical platform for a retailer by using open source tools R and RStudio along with SAP Sybase IQ database.
2. Key aspects included setting up SAP Sybase IQ as a column-store database for storage and querying of data, implementing R and RStudio for statistical analysis, and automating running of statistical models on new data.
3. The solution provided a low-cost platform capable of rapid prototyping of analytical models and production use for predictive analytics.
Data warehousing change in a challenging environmentDavid Walker
This white paper discusses the challenges of managing changes in a data warehousing environment. It describes a typical data warehouse architecture with source systems feeding data into a data warehouse and then into data marts or cubes. It also outlines the common processes involved like development, operations and data quality processes. The paper then discusses two major challenges - configuration/change management as there are frequent changes from source systems, applications and technologies that impact the data warehouse. The other challenge is managing and improving data quality as issues from source systems are often replicated in the data warehouse.
The document discusses six governance processes for data and business intelligence: data lifecycle, data models, data quality, data security, data warehousing, and metadata. For each process, it provides an overview of why governance is important in that area, and what the governance process will do to manage issues and ensure requirements are met. The governance processes aim to balance various factors, control changes, and provide oversight and accountability for data management.
How Real TIme Data Changes the Data Warehousemark madsen
Surveys show a growing demand for more up-to-date data in our BI environments. To meet these needs requires changing from a strict reliance on nightly batch-style ETL to other methods. What is often ignored is how this affects the data warehouse. This shift introduces new technology and methods, which means the warehouse must support new types of workloads.
• Methods and tools for processing up-to-date data
• New requirements for your data warehouse database or platform
• What to look for as you address these requirements
ETIS11 - Agile Business Intelligence - PresentationDavid Walker
The document discusses techniques for becoming more agile in business intelligence projects. It advocates for establishing small, skilled teams with strong user relationships and delegated authority. True agile organizations allow teams to operate outside standard corporate procedures and regularly deliver incremental improvements. Large organizations tend to prioritize processes and risk avoidance over agility, creativity, and benefits. Successful examples demonstrate recognizing the need to overcome bureaucracy through practices like Lockheed Martin's SkunkWorks model.
White paper making an-operational_data_store_(ods)_the_center_of_your_data_...Eric Javier Espino Man
The document discusses implementing an operational data store (ODS) to centralize data from multiple source systems. An ODS integrates disparate data for reporting and analytics while insulating operational systems. The document recommends selling an ODS internally by highlighting benefits like reduced workload for ETL developers and improved access to real-time data for business users. It also provides best practices like using automation tools that simplify ODS creation and maintenance.
These are the slides from my talk at Data Day Texas 2016 (#ddtx16).
The world of data warehousing has changed! With the advent of Big Data, Streaming Data, IoT, and The Cloud, what is a modern data management professional to do? It may seem to be a very different world with different concepts, terms, and techniques. Or is it? Lots of people still talk about having a data warehouse or several data marts across their organization. But what does that really mean today in 2016? How about the Corporate Information Factory (CIF), the Data Vault, an Operational Data Store (ODS), or just star schemas? Where do they fit now (or do they)? And now we have the Extended Data Warehouse (XDW) as well. How do all these things help us bring value and data-based decisions to our organizations? Where do Big Data and the Cloud fit? Is there a coherent architecture we can define? This talk will endeavor to cut through the hype and the buzzword bingo to help you figure out what part of this is helpful. I will discuss what I have seen in the real world (working and not working!) and a bit of where I think we are going and need to go in 2016 and beyond.
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...Edureka!
This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial:
1. What Is The Need For BI?
2. What Is Data Warehousing?
3. Key Terminologies Related To Data Warehouse Architecture:
a. OLTP Vs OLAP
b. ETL
c. Data Mart
d. Metadata
4. Data Warehouse Architecture
5. Demo: Creating A Data Warehouse
DAMA, Oregon Chapter, 2012 presentation - an introduction to Data Vault modeling. I will be covering parts of the methodology, comparison and contrast of issues in general for the EDW space. Followed by a brief technical introduction of the Data Vault modeling method.
After the presentation i I will be providing a demonstration of the ETL loading layers, LIVE!
You can find more on-line training at: http://LearnDataVault.com/training
Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...Denodo
This presentation has been extracted from a full webinar organized by Denodo. To learn more click here: http://bit.ly/1FOMD90
Big Data, Internet of Things, Data Lakes, Streaming Analytics, Machine Learning… these are just a few of the buzzwords being thrown around in the world of data management today. They provide us with new sources of data, new forms of analytics, and new ways of storing, managing and utilizing our data. The reality however, is that traditional Data Warehouse architectures are no longer able to handle many of these new technologies and a new data architecture is required.
So what does the new architecture look like? Does the enterprise data warehouse still have a role? Where do these new technologies fit in? How can business users easily and quickly access the various sources of data and analytic results at the right time to make the right decisions in this new world order?
Dr. Claudia Imhoff addresses these questions and presents the Extended Data Warehouse architecture (XDW), demonstrating the need for each component and how an enterprise combines these into appropriate workflows for proper decision support.
The document discusses databases versus data warehousing. It notes that databases are for operational purposes like storage and retrieval for applications, while data warehouses are used for informational purposes like business reporting and analysis. A data warehouse contains integrated, subject-oriented data from multiple sources that is used to support management decisions.
Can data virtualization uphold performance with complex queries?Denodo
Watch full webinar here: https://bit.ly/2JzypTx
There are myths about data virtualization that are based on misconceptions and even falsehoods. These myths can confuse and worry people who - quite rightly - look at data virtualization as a critical technology for a modern, agile data architecture.
We've decided that we need to set the record straight, so we put together this webinar series. It's time to bust a few myths!
In the first webinar of the series, we’ll be busting the 'performance' myth. “What about performance?” is usually the first question that we get when talking to people about data virtualization. After all, the data virtualization layer sits between you and your data, so how does this affect the performance of your queries? Sometimes the myth is perpetuated by people with alternative solutions…the ‘Put all your data in our Cloud and everything will be fine. Data virtualization? Nah, you don’t need that! It can't handle big queries anyway,’ type of thing.
Join us for this webinar to look at the basis of the 'performance' myth and examine whether there is any underlying truth to it.
The document discusses the purpose and history of data warehousing. It defines a data warehouse as a centralized, well-managed environment for storing high-value data from various sources. The data warehouse processes this data into a format optimized for analysis and information processing. The data warehouse has evolved from mainframe-based systems in the 1970s to today's cost-effective solutions embedded in software. A data warehouse is not defined by its size but by its functionality and ability to meet business objectives through consolidated, consistent data.
Govern and Protect Your End User InformationDenodo
Watch this Fast Data Strategy session with speakers Clinton Cohagan, Chief Enterprise Data Architect, Lawrence Livermore National Lab & Nageswar Cherukupalli, Vice President & Group Manager, Infosys here: https://buff.ly/2k8f8M5
In its recent report “Predictions 2018: A year of reckoning”, Forrester predicts that 80% of firms affected by GDPR will not comply with the regulation by May 2018. Of those noncompliant firms, 50% will intentionally not comply.
Compliance doesn’t have to be this difficult! What if you have an opportunity to facilitate compliance with a mature technology and significant cost reduction? Data virtualization is a mature, cost-effective technology that enables privacy by design to facilitate compliance.
Attend this session to learn:
• How data virtualization provides a compliance foundation with data catalog, auditing, and data security.
• How you can enable single enterprise-wide data access layer with guardrails.
• Why data virtualization is a must-have capability for compliance use cases.
• How Denodo’s customers have facilitated compliance.
PNB Bank implemented a data warehousing solution powered by Sybase IQ to address issues with their previous Teradata solution such as restrictions on scalability, inability to query and load data simultaneously, and queries not reflecting the most current data. Sybase IQ delivered faster query results using less infrastructure. Over 3 terabytes of data from 14 source systems was loaded into Sybase IQ in just 2 days, significantly faster than traditional systems. The migration was completed in under 3 months. Sybase IQ now supports over 150 concurrent users for PNB Bank without performance degradation.
A data warehouse is a central repository of historical data from an organization's various sources designed for analysis and reporting. It contains integrated data from multiple systems optimized for querying and analysis rather than transactions. Data is extracted, cleaned, and loaded from operational sources into the data warehouse periodically. The data warehouse uses a dimensional model to organize data into facts and dimensions for intuitive analysis and is optimized for reporting rather than transaction processing like operational databases. Data warehousing emerged to meet the growing demand for analysis that operational systems could not support due to impacts on performance and limitations in reporting capabilities.
Denodo Data Virtualization Platform: Overview (session 1 from Architect to Ar...Denodo
This is the first in a series of five webinars that look 'under the covers' of Denodo's industry leading Data Virtualization Platform. The webinar will provide an overview of the architecture and key modules of the Denodo Platform - subsequent webinars in the series will take a deeper look at some of the key modules and capabilities of the platform, including performance, scalability, security, and so on.
More information and FREE registrations to this webinar: http://goo.gl/fLi2bC
To learn more click to this link: http://go.denodo.com/a2a
Join the conversation at #Architect2Architect
Agenda:
The Denodo Platform
Platform Architecture
Key Modules
Connectors
Data Services and APIs
TAG is a technology process innovation and management consulting firm focused on reducing costs and adding value for clients. TAG provides end-to-end business process management services that integrate with clients' business models to improve agility, efficiency, and execution. TAG has expanded operations and sales representatives to the Dominican Republic and Panama.
Citizens Bank: Data Lake Implementation – Selecting BigInsights ViON Spark/Ha...Seeling Cheung
Citizens Bank was implementing a BigInsights Hadoop Data Lake with PureData System for Analytics to support all internal data initiatives and improve the customer experience. Testing BigInsights on the ViON Hadoop Appliance yielded the productivity, maintenance, and performance Citizens was looking for. Citizens Bank moved some analytics processing from Teradata to Netezza for better cost and performance, implemented BigInsights Hadoop for a data lake, and avoided large capital expenditures for additional Teradata capacity.
The document discusses data warehousing and describes its key characteristics and components. It defines a data warehouse as a copy of transaction data structured for querying and reporting to support strategic decision making. It outlines the stages of constructing a data warehouse including extraction, integration, and dimensional analysis to design the data warehouse database.
Enterprise resource planning system & data warehousing implementationSumya Abdelrazek
This document discusses Enterprise Resource Planning (ERP) systems and data warehousing implementation. It defines ERP as software that integrates all functions of an organization, including development, manufacturing, sales and marketing. ERP offers solutions for all business functions and packages for organizations of various sizes and types. Implementing ERP is complex, expensive and time-consuming. The document also defines data warehousing as an integrated, subject-oriented database that supports decision making. It discusses factors to consider for data warehousing implementation such as available funding, management views, and corporate culture.
This document provides an overview of data warehousing and online analytical processing (OLAP). It defines a data warehouse as a single, consistent store of subject-oriented data obtained from various sources to support end-user business analysis and decision-making. OLAP allows users to easily perform complex multidimensional analyses of data in areas such as comparisons, aggregations, and rankings. The document also discusses key aspects of data warehousing such as extraction, transformation, loading, and management of data from operational systems into the warehouse to support OLAP and decision support.
Logical Data Warehouse: The Foundation of Modern Data and Analytics (APAC)Denodo
Watch full webinar here: https://bit.ly/37KVoVs
According to a leading analyst firm, in 2019 the total spend in data and analytics was close to $104 billion! That number is expected to grow even more in 2020. Companies are investing in data warehouse modernization and data lake projects for descriptive and advanced analytics; however, for the analysis to be holistic, today’s architects weave disparate data streams together, not only from these analytical sources, but also from operational, third party, and streaming data sources. Logical data warehouse is a modern architectural methodology that virtually combines all the data across the enterprise and makes it available to analytical and visualization tools that facilitate timely, insightful, and impactful decisions throughout the enterprise.
In this session, you will learn:
- What is logical data warehouse and how to architect one
- The benefits of logical data warehouse – speed with agility
MapR on Azure: Getting Value from Big Data in the Cloud -MapR Technologies
Public cloud adoption is exploding and big data technologies are rapidly becoming an important driver of this growth. According to Wikibon, big data public cloud revenue will grow from 4.4% in 2016 to 24% of all big data spend by 2026. Digital transformation initiatives are now a priority for most organizations, with data and advanced analytics at the heart of enabling this change. This is key to driving competitive advantage in every industry.
There is nothing better than a real-world customer use case to help you understand how to get value from big data in the cloud and apply the learnings to your business. Join Microsoft, MapR, and Sullexis on November 10th to:
Hear from Sullexis on the business use case and technical implementation details of one of their oil & gas customers
Understand the integration points of the MapR Platform with other Azure services and why they matter
Know how to deploy the MapR Platform on the Azure cloud and get started easily
You will also get to hear about customer use cases of the MapR Converged Data Platform on Azure in other verticals such as real estate and retail.
Speakers
Rafael Godinho
Technical Evangelist
Microsoft Azure
Tim Morgan
Managing Director
Sullexis
Turning Petabytes of Data into Profit with Hadoop for the World’s Biggest Ret...Cloudera, Inc.
PRGX is the world's leading provider of accounts payable audit services and works with leading global retailers. As new forms of data started to flow into their organizations, standard RDBMS systems were not allowing them to scale. Now, by using Talend with Cloudera Enterprise, they are able to acheive a 9-10x performance benefit in processing data, reduce errors, and now provide more innovative products and services to end customers.
Watch this webinar to learn how PRGX worked with Cloudera and Talend to create a high-performance computing platform for data analytics and discovery that rapidly allows them to process, model, and serve massive amount of structured and unstructured data.
ETIS11 - Agile Business Intelligence - PresentationDavid Walker
The document discusses techniques for becoming more agile in business intelligence projects. It advocates for establishing small, skilled teams with strong user relationships and delegated authority. True agile organizations allow teams to operate outside standard corporate procedures and regularly deliver incremental improvements. Large organizations tend to prioritize processes and risk avoidance over agility, creativity, and benefits. Successful examples demonstrate recognizing the need to overcome bureaucracy through practices like Lockheed Martin's SkunkWorks model.
White paper making an-operational_data_store_(ods)_the_center_of_your_data_...Eric Javier Espino Man
The document discusses implementing an operational data store (ODS) to centralize data from multiple source systems. An ODS integrates disparate data for reporting and analytics while insulating operational systems. The document recommends selling an ODS internally by highlighting benefits like reduced workload for ETL developers and improved access to real-time data for business users. It also provides best practices like using automation tools that simplify ODS creation and maintenance.
These are the slides from my talk at Data Day Texas 2016 (#ddtx16).
The world of data warehousing has changed! With the advent of Big Data, Streaming Data, IoT, and The Cloud, what is a modern data management professional to do? It may seem to be a very different world with different concepts, terms, and techniques. Or is it? Lots of people still talk about having a data warehouse or several data marts across their organization. But what does that really mean today in 2016? How about the Corporate Information Factory (CIF), the Data Vault, an Operational Data Store (ODS), or just star schemas? Where do they fit now (or do they)? And now we have the Extended Data Warehouse (XDW) as well. How do all these things help us bring value and data-based decisions to our organizations? Where do Big Data and the Cloud fit? Is there a coherent architecture we can define? This talk will endeavor to cut through the hype and the buzzword bingo to help you figure out what part of this is helpful. I will discuss what I have seen in the real world (working and not working!) and a bit of where I think we are going and need to go in 2016 and beyond.
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...Edureka!
This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial:
1. What Is The Need For BI?
2. What Is Data Warehousing?
3. Key Terminologies Related To Data Warehouse Architecture:
a. OLTP Vs OLAP
b. ETL
c. Data Mart
d. Metadata
4. Data Warehouse Architecture
5. Demo: Creating A Data Warehouse
DAMA, Oregon Chapter, 2012 presentation - an introduction to Data Vault modeling. I will be covering parts of the methodology, comparison and contrast of issues in general for the EDW space. Followed by a brief technical introduction of the Data Vault modeling method.
After the presentation i I will be providing a demonstration of the ETL loading layers, LIVE!
You can find more on-line training at: http://LearnDataVault.com/training
Extended Data Warehouse - A New Data Architecture for Modern BI with Claudia ...Denodo
This presentation has been extracted from a full webinar organized by Denodo. To learn more click here: http://bit.ly/1FOMD90
Big Data, Internet of Things, Data Lakes, Streaming Analytics, Machine Learning… these are just a few of the buzzwords being thrown around in the world of data management today. They provide us with new sources of data, new forms of analytics, and new ways of storing, managing and utilizing our data. The reality however, is that traditional Data Warehouse architectures are no longer able to handle many of these new technologies and a new data architecture is required.
So what does the new architecture look like? Does the enterprise data warehouse still have a role? Where do these new technologies fit in? How can business users easily and quickly access the various sources of data and analytic results at the right time to make the right decisions in this new world order?
Dr. Claudia Imhoff addresses these questions and presents the Extended Data Warehouse architecture (XDW), demonstrating the need for each component and how an enterprise combines these into appropriate workflows for proper decision support.
The document discusses databases versus data warehousing. It notes that databases are for operational purposes like storage and retrieval for applications, while data warehouses are used for informational purposes like business reporting and analysis. A data warehouse contains integrated, subject-oriented data from multiple sources that is used to support management decisions.
Can data virtualization uphold performance with complex queries?Denodo
Watch full webinar here: https://bit.ly/2JzypTx
There are myths about data virtualization that are based on misconceptions and even falsehoods. These myths can confuse and worry people who - quite rightly - look at data virtualization as a critical technology for a modern, agile data architecture.
We've decided that we need to set the record straight, so we put together this webinar series. It's time to bust a few myths!
In the first webinar of the series, we’ll be busting the 'performance' myth. “What about performance?” is usually the first question that we get when talking to people about data virtualization. After all, the data virtualization layer sits between you and your data, so how does this affect the performance of your queries? Sometimes the myth is perpetuated by people with alternative solutions…the ‘Put all your data in our Cloud and everything will be fine. Data virtualization? Nah, you don’t need that! It can't handle big queries anyway,’ type of thing.
Join us for this webinar to look at the basis of the 'performance' myth and examine whether there is any underlying truth to it.
The document discusses the purpose and history of data warehousing. It defines a data warehouse as a centralized, well-managed environment for storing high-value data from various sources. The data warehouse processes this data into a format optimized for analysis and information processing. The data warehouse has evolved from mainframe-based systems in the 1970s to today's cost-effective solutions embedded in software. A data warehouse is not defined by its size but by its functionality and ability to meet business objectives through consolidated, consistent data.
Govern and Protect Your End User InformationDenodo
Watch this Fast Data Strategy session with speakers Clinton Cohagan, Chief Enterprise Data Architect, Lawrence Livermore National Lab & Nageswar Cherukupalli, Vice President & Group Manager, Infosys here: https://buff.ly/2k8f8M5
In its recent report “Predictions 2018: A year of reckoning”, Forrester predicts that 80% of firms affected by GDPR will not comply with the regulation by May 2018. Of those noncompliant firms, 50% will intentionally not comply.
Compliance doesn’t have to be this difficult! What if you have an opportunity to facilitate compliance with a mature technology and significant cost reduction? Data virtualization is a mature, cost-effective technology that enables privacy by design to facilitate compliance.
Attend this session to learn:
• How data virtualization provides a compliance foundation with data catalog, auditing, and data security.
• How you can enable single enterprise-wide data access layer with guardrails.
• Why data virtualization is a must-have capability for compliance use cases.
• How Denodo’s customers have facilitated compliance.
PNB Bank implemented a data warehousing solution powered by Sybase IQ to address issues with their previous Teradata solution such as restrictions on scalability, inability to query and load data simultaneously, and queries not reflecting the most current data. Sybase IQ delivered faster query results using less infrastructure. Over 3 terabytes of data from 14 source systems was loaded into Sybase IQ in just 2 days, significantly faster than traditional systems. The migration was completed in under 3 months. Sybase IQ now supports over 150 concurrent users for PNB Bank without performance degradation.
A data warehouse is a central repository of historical data from an organization's various sources designed for analysis and reporting. It contains integrated data from multiple systems optimized for querying and analysis rather than transactions. Data is extracted, cleaned, and loaded from operational sources into the data warehouse periodically. The data warehouse uses a dimensional model to organize data into facts and dimensions for intuitive analysis and is optimized for reporting rather than transaction processing like operational databases. Data warehousing emerged to meet the growing demand for analysis that operational systems could not support due to impacts on performance and limitations in reporting capabilities.
Denodo Data Virtualization Platform: Overview (session 1 from Architect to Ar...Denodo
This is the first in a series of five webinars that look 'under the covers' of Denodo's industry leading Data Virtualization Platform. The webinar will provide an overview of the architecture and key modules of the Denodo Platform - subsequent webinars in the series will take a deeper look at some of the key modules and capabilities of the platform, including performance, scalability, security, and so on.
More information and FREE registrations to this webinar: http://goo.gl/fLi2bC
To learn more click to this link: http://go.denodo.com/a2a
Join the conversation at #Architect2Architect
Agenda:
The Denodo Platform
Platform Architecture
Key Modules
Connectors
Data Services and APIs
TAG is a technology process innovation and management consulting firm focused on reducing costs and adding value for clients. TAG provides end-to-end business process management services that integrate with clients' business models to improve agility, efficiency, and execution. TAG has expanded operations and sales representatives to the Dominican Republic and Panama.
Citizens Bank: Data Lake Implementation – Selecting BigInsights ViON Spark/Ha...Seeling Cheung
Citizens Bank was implementing a BigInsights Hadoop Data Lake with PureData System for Analytics to support all internal data initiatives and improve the customer experience. Testing BigInsights on the ViON Hadoop Appliance yielded the productivity, maintenance, and performance Citizens was looking for. Citizens Bank moved some analytics processing from Teradata to Netezza for better cost and performance, implemented BigInsights Hadoop for a data lake, and avoided large capital expenditures for additional Teradata capacity.
The document discusses data warehousing and describes its key characteristics and components. It defines a data warehouse as a copy of transaction data structured for querying and reporting to support strategic decision making. It outlines the stages of constructing a data warehouse including extraction, integration, and dimensional analysis to design the data warehouse database.
Enterprise resource planning system & data warehousing implementationSumya Abdelrazek
This document discusses Enterprise Resource Planning (ERP) systems and data warehousing implementation. It defines ERP as software that integrates all functions of an organization, including development, manufacturing, sales and marketing. ERP offers solutions for all business functions and packages for organizations of various sizes and types. Implementing ERP is complex, expensive and time-consuming. The document also defines data warehousing as an integrated, subject-oriented database that supports decision making. It discusses factors to consider for data warehousing implementation such as available funding, management views, and corporate culture.
This document provides an overview of data warehousing and online analytical processing (OLAP). It defines a data warehouse as a single, consistent store of subject-oriented data obtained from various sources to support end-user business analysis and decision-making. OLAP allows users to easily perform complex multidimensional analyses of data in areas such as comparisons, aggregations, and rankings. The document also discusses key aspects of data warehousing such as extraction, transformation, loading, and management of data from operational systems into the warehouse to support OLAP and decision support.
Logical Data Warehouse: The Foundation of Modern Data and Analytics (APAC)Denodo
Watch full webinar here: https://bit.ly/37KVoVs
According to a leading analyst firm, in 2019 the total spend in data and analytics was close to $104 billion! That number is expected to grow even more in 2020. Companies are investing in data warehouse modernization and data lake projects for descriptive and advanced analytics; however, for the analysis to be holistic, today’s architects weave disparate data streams together, not only from these analytical sources, but also from operational, third party, and streaming data sources. Logical data warehouse is a modern architectural methodology that virtually combines all the data across the enterprise and makes it available to analytical and visualization tools that facilitate timely, insightful, and impactful decisions throughout the enterprise.
In this session, you will learn:
- What is logical data warehouse and how to architect one
- The benefits of logical data warehouse – speed with agility
MapR on Azure: Getting Value from Big Data in the Cloud -MapR Technologies
Public cloud adoption is exploding and big data technologies are rapidly becoming an important driver of this growth. According to Wikibon, big data public cloud revenue will grow from 4.4% in 2016 to 24% of all big data spend by 2026. Digital transformation initiatives are now a priority for most organizations, with data and advanced analytics at the heart of enabling this change. This is key to driving competitive advantage in every industry.
There is nothing better than a real-world customer use case to help you understand how to get value from big data in the cloud and apply the learnings to your business. Join Microsoft, MapR, and Sullexis on November 10th to:
Hear from Sullexis on the business use case and technical implementation details of one of their oil & gas customers
Understand the integration points of the MapR Platform with other Azure services and why they matter
Know how to deploy the MapR Platform on the Azure cloud and get started easily
You will also get to hear about customer use cases of the MapR Converged Data Platform on Azure in other verticals such as real estate and retail.
Speakers
Rafael Godinho
Technical Evangelist
Microsoft Azure
Tim Morgan
Managing Director
Sullexis
Turning Petabytes of Data into Profit with Hadoop for the World’s Biggest Ret...Cloudera, Inc.
PRGX is the world's leading provider of accounts payable audit services and works with leading global retailers. As new forms of data started to flow into their organizations, standard RDBMS systems were not allowing them to scale. Now, by using Talend with Cloudera Enterprise, they are able to acheive a 9-10x performance benefit in processing data, reduce errors, and now provide more innovative products and services to end customers.
Watch this webinar to learn how PRGX worked with Cloudera and Talend to create a high-performance computing platform for data analytics and discovery that rapidly allows them to process, model, and serve massive amount of structured and unstructured data.
Not Just a necessary evil, it’s good for business: implementing PCI DSS contr...DataWorks Summit
For firms in the financial industry, especially within regulated organizations such as credit card processors and banks, PCI DSS compliance has become a business and operational necessity. Although the blueprint of a PCI-compliant architecture varies from organization to organization, the mixture of modern Hadoop-based data lakes and legacy systems are a common theme.
In this talk, we will discuss recent updates to PCI DSS and how significant portions of PCI DSS compliance controls can be achieved using open source Hadoop security stack and technologies for the Hadoop ecosystem. We will provide a broad overview of implementing key aspects of PCI DSS standards at WorldPay such as encryption management, data protection with anonymization, separation of duties, and deployment considerations regarding securing the Hadoop clusters at the network layer from a practitioner’s perspective. The talk will provide patterns and practices map current Hadoop security capabilities to security controls that a PCI-compliant environment requires.
Speaker
David Walker, Enterprise Data Platform Programme Director, Worldpay
Srikanth Venkat, Senior Director Product Management, Hortonworks
Data Works Berlin 2018 - Worldpay - PCI ComplianceDavid Walker
A presentation from the Data Works conference in 2018 that looks how Worldpay, a major payments provider, deployed a secure Hadoop cluster in order to meet business requirements and in the process became on e of the few fully certified PCI compliance clusters in the world
Nov 2014 talk to SW Data Meetup by Mike Olson, co-founder and chairman of Cloudera.
In business, we often deal with hype around trends in society, politics, economy and technology. We know we need to take claims of the next big thing with a grain of salt and that we should be careful not to set expectations too high. However, with Big Data analytics, the opposite is true. The hype that accompanies it actually conceals the enormity of its impact on the way we do business. In this talk I’ll discuss how new 'Data Driven' economies are emerging through relentless innovation across the public and private sectors.
Mike (co-founded Cloudera in 2008 and served as its CEO until 2013 when he took on his current role of chief strategy officer (CSO.) As CSO, Mike is responsible for Cloudera’s product strategy, open source leadership, engineering alignment and direct engagement with customers. Prior to Cloudera Mike was CEO of Sleepycat Software, makers of Berkeley DB, the open source embedded database engine. Mike spent two years at Oracle Corporation as vice president for Embedded Technologies after Oracle’s acquisition of Sleepycat in 2006. Prior to joining Sleepycat, Mike held technical and business positions at database vendors Britton Lee, Illustra Information Technologies and Informix Software. Mike has a Bachelor’s and a Master’s Degree in Computer Science from the University of California, Berkeley.
Watch this webinar in full here: https://buff.ly/2MVTKqL
Self-Service BI promises to remove the bottleneck that exists between IT and business users. The truth is, if data is handed over to a wide range of data consumers without proper guardrails in place, it can result in data anarchy.
Attend this session to learn why data virtualization:
• Is a must for implementing the right self-service BI
• Makes self-service BI useful for every business user
• Accelerates any self-service BI initiative
Gain Deep Visibility into APIs and Integrations with Anypoint MonitoringInfluxData
On average, a business supporting digital transactions now crosses 35 backend systems—and legacy tools haven’t been able to keep up. This session will cover how MuleSoft uses InfluxCloud to help power their monitoring and diagnostic solutions as well as provide end-to-end actionable visibility to APIs and integrations to help customers identify and resolve issues quickly.
Simply Business is a leading insurance provider for small business in the UK and we are now growing to the USA. In this presentation, I explain how our data platform is evolving to keep delivering value and adapting to a company that changes really fast.
Redefining the Role of IT in a Self-Help Data Integration EnvironmentUNIFI Software
Sabre is a technology solutions provider to the global travel and tourism industry. As part of delivering that service, Sabre has Service Level Agreements with each Airline client. Maintaining accurate records of those SLAs and understanding escalations falls to the IT support team. Madhuri Kollu, at Sabre, will provide insight into how they integrate legacy and new data sources and provide business leaders the tools to derive critical business insights from the data.
Hadoop in 2015: Keys to Achieving Operational Excellence for the Real-Time En...MapR Technologies
In this webinar, Carl W. Olofson, Research Vice President, Application Development and Deployment for IDC, and Dale Kim, Director of Industry Solutions for MapR, will provide an insightful outlook for Hadoop in 2015, and will outline why enterprises should consider using Hadoop as a "Decision Data Platform" and how it can function as a single platform for both online transaction processing (OLTP) and real-time analytics.
8 Things to Consider as SharePoint Moves to the CloudChristian Buckley
A review of the changes happening inside the SharePoint platform and throughout the industry as more and more organizations begin to develop their cloud strategies. This presentation provides some guidance on how to develop your own cloud strategy. Initially presented at IT Pro Camp DC, Feb 2014.
As many industries, banking is undergoing a fundamental change because of the software revolution. No longer are banks competing only on interest rates and having the best traders, these days customer experience and having the best engineers are the focus. In this changing world, banks compete with new start-ups, the so-called Fintechs, and with large platform organisations such as Google, Facebook and Apple. At ING, we believe that staying ahead of the game means changing how we interact with our customers, no longer a traditional model of waiting for the customers to come to the bank through our website or apps, but to actively reach out to the customer with information that is relevant to him or her in order to make their financial life frictionless. Many of these changes are driven by reacting to all events that are relevant to the customer, and using streaming analytics to be able to reach out to the customer in milliseconds after the event occurs. Apache Flink is key for ING to achieve this. This presentation addresses how ING approaches the challenge, the role that Apache Flink plays, and the consequences regulations have on how we work with Open Source in general, and with Apache Flink (and data Artisans) in particular. This keynote takes place at Kino 3.
Use Cases from Batch to Streaming, MapReduce to Spark, Mainframe to Cloud: To...Precisely
This document discusses how Syncsort helps companies access and integrate data from various sources to power analytics. It provides examples of how Syncsort has helped companies in insurance, media, and hotels easily onboard and integrate both historical and streaming data from multiple sources like mainframes, databases, and IoT devices. This allows for faster insights, increased productivity, cost savings, and helps future proof applications.
Keyrus is a data analytics consultancy that helps customers make data-driven decisions. It provides services including big data solutions, data management strategies, data integration, business intelligence dashboards, predictive analytics, and data science consulting. Keyrus has expertise in structured and unstructured data, data discovery visualization tools, and building end-to-end analytics solutions. Sample projects include building Hadoop environments for large telecom data and creating risk monitoring dashboards for investment banks.
Keyrus is a data analytics consultancy that helps customers make data-driven decisions. It provides services including big data solutions, data management strategies, data integration, machine learning, predictive analytics, and data visualization dashboards. Keyrus consultants have skills in databases, data modeling, programming, and business requirements. For example, for a bank, Keyrus built interactive dashboards from multiple databases to provide regulators with risk monitoring dashboards.
How to scale your PaaS with OVH infrastructure?OVHcloud
ForePaaS provides a platform for data infrastructure automation that allows customers to collect, store, transform and analyze data across multiple cloud providers or on-premise in a unified manner. Key features of the ForePaaS platform include being end-to-end, multi-cloud, providing a marketplace for sharing elements of work, and offering automated infrastructure that scales based on customer needs. ForePaaS has partnered with OVH to leverage their public cloud, private cloud, and bare metal server offerings to power ForePaaS infrastructure globally.
InfoSphere BigInsights is IBM's distribution of Hadoop that:
- Enhances ease of use and usability for both technical and non-technical users.
- Includes additional tools, technologies, and accelerators to simplify developing and running analytics on Hadoop.
- Aims to help users gain business insights from their data more quickly through an integrated platform.
The document provides an overview of IBM's BigInsights product. It discusses how BigInsights can help businesses gain insights from large, complex datasets through features like built-in text analytics, SQL support, spreadsheet-style analysis, and accelerators for domain-specific analytics like social media. The document also summarizes capabilities of BigInsights like Big SQL, Big Sheets, Big R, and its text analytics engine that allow businesses to explore, analyze, and model large datasets.
The document provides an overview of IBM's BigInsights product. It discusses how BigInsights can help businesses gain insights from large, complex datasets through features like built-in text analytics, SQL support, spreadsheet-style analysis, and accelerators for domain-specific analytics like social media. The document also summarizes capabilities of BigInsights like Big SQL, Big Sheets, Big R, and its embedded text analytics engine.
Big Data Analytics 2017 - Worldpay - Empowering PaymentsDavid Walker
A presentation from the Big Data Analytics conference in 2017 that looks how Worldpay, a major payments provider, uses data science and big data analytics to influence successful card payments.
A discussion on how insurance companies could use telematics data, social media and open data sources to analyse and better price policies for their customers
Data Driven Insurance Underwriting (Dutch Language Version)David Walker
A discussion on how insurance companies could use telematics data, social media and open data sources to analyse and better price policies for their customers
An introduction to data virtualization in business intelligenceDavid Walker
A brief description of what Data Virtualisation is and how it can be used to support business intelligence applications and development. Originally presented to the ETIS Conference in Riga, Latvia in October 2013
A presentation to the ETIS Business Intelligence & Data Warehousing Working Group in Brussels 22-Mar-13 discussing what Saas & Cloud means and how they will affect BI in Telcos
Gathering Business Requirements for Data WarehousesDavid Walker
This document provides an overview of the process for gathering business requirements for a data management and warehousing project. It discusses why requirements are gathered, the types of requirements needed, how business processes create data in the form of dimensions and measures, and how the gathered requirements will be used to design reports to meet business needs. A straw-man proposal is presented as a starting point for further discussion.
Building a data warehouse of call data recordsDavid Walker
This document discusses considerations for building a data warehouse to archive call detail records (CDRs) for a mobile virtual network operator (MVNO). The MVNO needed to improve compliance with data retention laws and enable more flexible analysis of CDR data. Key factors examined were whether to use Hadoop/NoSQL solutions and relational databases. While Hadoop can handle unstructured data, the CDRs have a defined structure and the IT team lacked NoSQL skills, so a relational database was deemed more suitable.
Those responsible for data management often struggle due to the many responsibilities involved. While organizations recognize data as a key asset, they are often unable to properly manage it. Creating a "Literal Staging Area" or LSA platform can help take a holistic view of improving overall data management. An LSA makes a copy of business systems that is refreshed daily and can be used for tasks like data quality monitoring, analysis, and operational reporting to help address data management challenges in a cost effective way for approximately $120,000.
A linux mac os x command line interfaceDavid Walker
This document describes a Linux/Mac OS X command line interface for interacting with the AffiliateWindow API. It provides scripts that allow sending API requests via cURL or Wget from the command line. The scripts read an XML request file, send it to the AffiliateWindow API server, and write the response to an XML file. This provides an alternative to PHP for accessing the API from the command line for testing, auditing, or using other development tools.
Connections a life in the day of - david walkerDavid Walker
David Walker is a Principal Consultant who leads large data warehousing projects with staff sizes between 1 to 20 people. He enjoys rugby and spends time with his family in Dorset when not traveling for work. The document provides biographical details about Walker's background, responsibilities, interests, and perspectives on technology and business challenges.
Conspectus data warehousing appliances – fad or futureDavid Walker
Data warehousing appliances aim to simplify and accelerate the process of extracting, transforming, and loading data from multiple source systems into a dedicated database for analysis. Traditional data warehousing systems are complex and expensive to implement and maintain over time as data volumes increase. Data warehousing appliances use commodity hardware and specialized database engines to radically reduce data loading times, improve query performance, and simplify administration. While appliances introduce new challenges around proprietary technologies and credibility of performance claims, organizations that have implemented them report major gains in query speed and storage efficiency with reduced support costs. As more vendors enter the market, appliances are poised to become a key part of many organizations' data warehousing strategies.
Using the right data model in a data martDavid Walker
A presentation describing how to choose the right data model design for your data mart. Discusses the pros and benefits of different data models with different rdbms technologies and tools
The document discusses spatial data and analysis. It defines spatial data as information that can be analyzed based on geographic context, such as locations, distances and boundaries. It then describes the three common types of spatial data - points, lines and polygons - and how they are used to answer questions about proximity and relationships between objects. Finally, it outlines some of the key sources for spatial data, challenges in working with spatial data, and provides a model for how to deliver spatial data and analysis.
UKOUG06 - An Introduction To Process Neutral Data Modelling - PresentationDavid Walker
Data Management & Warehousing is a consulting firm that specializes in enterprise data warehousing. The document discusses process neutral data modeling, which is a technique for designing data warehouse models that are less impacted by changes in source systems or business processes. It does this by incorporating metadata into the data model similar to how XML includes metadata in data files. The approach defines major entities, their types and properties, relationships between entities, and occurrences to model interactions between entities in a consistent way that supports managing changes.
Oracle BI06 From Volume To Value - PresentationDavid Walker
The document discusses challenges with a European mobile telco's data warehouse that contains over 150 billion call detail records. It takes too long to get answers from the data warehouse and it is underutilized. The document recommends establishing quick service teams, performing data profiling and cleansing, integrating the data warehouse into business processes, using business information portals, and RSS feeds to address engagement, user, and technical issues. This will help users get timely, accurate information and increase adoption of the data warehouse.
IRM09 - What Can IT Really Deliver For BI and DW - PresentationDavid Walker
This document summarizes a discussion between the Data Management and Carehousing business about delivering Business Intelligence. Some of the key points covered include:
1. The business has substantial front-loaded costs to pay for Business Intelligence and Carehousing. There are also ongoing costs for system changes and maintenance.
2. The business must understand that Business Intelligence is an ongoing, long-term development and not a one-off project.
3. It is important for the business and IT to agree on what a successful Business Intelligence solution would look like.
ETIS10 - BI Governance Models & Strategies - PresentationDavid Walker
The document discusses business intelligence (BI) governance models and strategies. It defines BI governance and outlines key components of a BI governance framework, including the executive steering committee, programme management, user forums, certification committees, project management, implementation teams, and exploitation teams. It also discusses the importance of data modeling, data quality, data warehousing development, and data security and lifecycle management processes to a well-governed BI program.
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
What is an RPA CoE? Session 1 – CoE VisionDianaGray10
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.
"NATO Hackathon Winner: AI-Powered Drug Search", Taras KlobaFwdays
This is a session that details how PostgreSQL's features and Azure AI Services can be effectively used to significantly enhance the search functionality in any application.
In this session, we'll share insights on how we used PostgreSQL to facilitate precise searches across multiple fields in our mobile application. The techniques include using LIKE and ILIKE operators and integrating a trigram-based search to handle potential misspellings, thereby increasing the search accuracy.
We'll also discuss how the azure_ai extension on PostgreSQL databases in Azure and Azure AI Services were utilized to create vectors from user input, a feature beneficial when users wish to find specific items based on text prompts. While our application's case study involves a drug search, the techniques and principles shared in this session can be adapted to improve search functionality in a wide range of applications. Join us to learn how PostgreSQL and Azure AI can be harnessed to enhance your application's search capability.
From Natural Language to Structured Solr Queries using LLMsSease
This talk draws on experimentation to enable AI applications with Solr. One important use case is to use AI for better accessibility and discoverability of the data: while User eXperience techniques, lexical search improvements, and data harmonization can take organizations to a good level of accessibility, a structural (or “cognitive” gap) remains between the data user needs and the data producer constraints.
That is where AI – and most importantly, Natural Language Processing and Large Language Model techniques – could make a difference. This natural language, conversational engine could facilitate access and usage of the data leveraging the semantics of any data source.
The objective of the presentation is to propose a technical approach and a way forward to achieve this goal.
The key concept is to enable users to express their search queries in natural language, which the LLM then enriches, interprets, and translates into structured queries based on the Solr index’s metadata.
This approach leverages the LLM’s ability to understand the nuances of natural language and the structure of documents within Apache Solr.
The LLM acts as an intermediary agent, offering a transparent experience to users automatically and potentially uncovering relevant documents that conventional search methods might overlook. The presentation will include the results of this experimental work, lessons learned, best practices, and the scope of future work that should improve the approach and make it production-ready.
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...Fwdays
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host