Explores pros and cons of current OLAP technologies, new generation visualization tools, in-memory databases and OLAP for big data. We also discuss real-life client scenarios for a pragmatic perspective. View the video recording and download this deck at: http://www.senturus.com/resources/is-olap-dead/
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Step-1 Tableau Introduction
Step-2 Connecting to Data
Step-3 Building basic views
Step-4 Data manipulations and Calculated fields
Step-5 Tableau Dashboards
Step-6 Advanced Data Options
Step-7 Advanced graph Options
ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...DATAVERSITY
Thirty years is a long time for a technology foundation to be as active as relational databases. Are their replacements here? In this webinar, we say no.
Databases have not sat around while Hadoop emerged. The Hadoop era generated a ton of interest and confusion, but is it still relevant as organizations are deploying cloud storage like a kid in a candy store? We’ll discuss what platforms to use for what data. This is a critical decision that can dictate two to five times additional work effort if it’s a bad fit.
Drop the herd mentality. In reality, there is no “one size fits all” right now. We need to make our platform decisions amidst this backdrop.
This webinar will distinguish these analytic deployment options and help you platform 2020 and beyond for success.
Beyond PowerPlay: Choose the Right OLAP Tool for Your BI Environment (Cognos...Senturus
Feature differences between OLAP tools used for BI applications, including Dynamic Cubes. View the webinar video recording and download this deck: http://www.senturus.com/resources/beyond-powerplay-choosing-right-olap-tool-bi-environment/
This presentation outlines important criteria that should be considered before investing significant hours (and dollars) in development of OLAP tools. As always, we give a candid review of relevant tool capabilities, show features in action and provide some pragmatic decision-making tips on how to make the right choice for your BI environment.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Top 10 Tips for an Effective Postgres DeploymentEDB
This presentation addresses these key questions during your Postgres deployment:
* What is this database going to be used for – a reporting server or data warehouse, or as an operational database supporting an application?
* Which resources should I spend the budget on to ensure optimal database performance – bigger servers, more CPUs/cores, disks, or more memory?
* What are my backup requirements? If I ever need to restore, how far back do I need to go and what will that mean to the business?
* How will I handle any hot fixes, such as security patches?
* What downtime can be afforded and what processes need to be in place to apply critical or maintenance updates?
* What are my replication and failover requirements and what should I do for my high availability configuration?
The answers to these questions will impact how well you prepare, configure, and tune your database environment. The consequences of overlooking the key ingredients of your deployment can result in misallocated resources, limited ability to change, or worse - facing an outage with critical data loss.
With solid Postgres deployment planning, you can reduce risks, spend less time troubleshooting in post-production situations, lower long-term maintenance costs, instill confidence, and be a superstar DBA.
****************************************
This presentation is helpful for DBAs, Data Architects, IT Managers, IT Directors, and IT Strategists who are responsible for supporting Postgres-based applications and deployment with ongoing maintenance of Postgres databases. It is equally suitable for organizations using community PostgreSQL as well as EDB’s Postgres Plus product family.
Architecting Agile Data Applications for ScaleDatabricks
Data analytics and reporting platforms historically have been rigid, monolithic, hard to change and have limited ability to scale up or scale down. I can’t tell you how many times I have heard a business user ask for something as simple as an additional column in a report and IT says it will take 6 months to add that column because it doesn’t exist in the datawarehouse. As a former DBA, I can tell you the countless hours I have spent “tuning” SQL queries to hit pre-established SLAs. This talk will talk about how to architect modern data and analytics platforms in the cloud to support agility and scalability. We will include topics like end to end data pipeline flow, data mesh and data catalogs, live data and streaming, performing advanced analytics, applying agile software development practices like CI/CD and testability to data applications and finally taking advantage of the cloud for infinite scalability both up and down.
Step-1 Tableau Introduction
Step-2 Connecting to Data
Step-3 Building basic views
Step-4 Data manipulations and Calculated fields
Step-5 Tableau Dashboards
Step-6 Advanced Data Options
Step-7 Advanced graph Options
ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...DATAVERSITY
Thirty years is a long time for a technology foundation to be as active as relational databases. Are their replacements here? In this webinar, we say no.
Databases have not sat around while Hadoop emerged. The Hadoop era generated a ton of interest and confusion, but is it still relevant as organizations are deploying cloud storage like a kid in a candy store? We’ll discuss what platforms to use for what data. This is a critical decision that can dictate two to five times additional work effort if it’s a bad fit.
Drop the herd mentality. In reality, there is no “one size fits all” right now. We need to make our platform decisions amidst this backdrop.
This webinar will distinguish these analytic deployment options and help you platform 2020 and beyond for success.
Beyond PowerPlay: Choose the Right OLAP Tool for Your BI Environment (Cognos...Senturus
Feature differences between OLAP tools used for BI applications, including Dynamic Cubes. View the webinar video recording and download this deck: http://www.senturus.com/resources/beyond-powerplay-choosing-right-olap-tool-bi-environment/
This presentation outlines important criteria that should be considered before investing significant hours (and dollars) in development of OLAP tools. As always, we give a candid review of relevant tool capabilities, show features in action and provide some pragmatic decision-making tips on how to make the right choice for your BI environment.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Top 10 Tips for an Effective Postgres DeploymentEDB
This presentation addresses these key questions during your Postgres deployment:
* What is this database going to be used for – a reporting server or data warehouse, or as an operational database supporting an application?
* Which resources should I spend the budget on to ensure optimal database performance – bigger servers, more CPUs/cores, disks, or more memory?
* What are my backup requirements? If I ever need to restore, how far back do I need to go and what will that mean to the business?
* How will I handle any hot fixes, such as security patches?
* What downtime can be afforded and what processes need to be in place to apply critical or maintenance updates?
* What are my replication and failover requirements and what should I do for my high availability configuration?
The answers to these questions will impact how well you prepare, configure, and tune your database environment. The consequences of overlooking the key ingredients of your deployment can result in misallocated resources, limited ability to change, or worse - facing an outage with critical data loss.
With solid Postgres deployment planning, you can reduce risks, spend less time troubleshooting in post-production situations, lower long-term maintenance costs, instill confidence, and be a superstar DBA.
****************************************
This presentation is helpful for DBAs, Data Architects, IT Managers, IT Directors, and IT Strategists who are responsible for supporting Postgres-based applications and deployment with ongoing maintenance of Postgres databases. It is equally suitable for organizations using community PostgreSQL as well as EDB’s Postgres Plus product family.
Architecting Agile Data Applications for ScaleDatabricks
Data analytics and reporting platforms historically have been rigid, monolithic, hard to change and have limited ability to scale up or scale down. I can’t tell you how many times I have heard a business user ask for something as simple as an additional column in a report and IT says it will take 6 months to add that column because it doesn’t exist in the datawarehouse. As a former DBA, I can tell you the countless hours I have spent “tuning” SQL queries to hit pre-established SLAs. This talk will talk about how to architect modern data and analytics platforms in the cloud to support agility and scalability. We will include topics like end to end data pipeline flow, data mesh and data catalogs, live data and streaming, performing advanced analytics, applying agile software development practices like CI/CD and testability to data applications and finally taking advantage of the cloud for infinite scalability both up and down.
SAP #BOBJ #BI 4.1 Upgrade Webcast Series 3: BI 4.1 Sizing and VirtualizationSAP Analytics
http://spr.ly/BI41_Migration_Webinars - Learn how to develop a good strategy for sizing your SAP BusinessObjects BI 4.1 deployment. Understand why core architectural differences between former BOE XI releases and BI 4.1 mandate new sizing considerations. Find out how to test and tune your BI system before releasing it to your user base. Also, learn about virtualization support and guidelines when deploying to virtual and cloud environments.
• Understand how and where virtualization works well
• Learn how to avoid difficult situations when managing virtualized resources
• Develop a strategy that allows for growth, and talk the same language as your administrators
For more on upgrading to SAP BusinessObjects BI 4.1, visit http://www.sapbusinessobjectsbi.com
IBM Cognos Analytics Release 7+ Authoring Improvements: Demos of New and Rein...Senturus
Add interactivity to reports with OLAP data, create briefing book-style reports based on existing reports using report references and tables of contents, use the report pages framework to combine presentations into a single report and increase efficiency in report building. View the video recording and download this deck at: http://www.senturus.com/resources/cool-improvements-for-report-developers-in-cognos-analytics-r7/.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Options for Data Prep - A Survey of the Current MarketDremio Corporation
Data comes in many shapes and sizes, and every company struggles to find ways to transform, validate, and enrich data for multiple purposes. The problem has been around as long as data, and the market has an overwhelming number of options. In this presentation we look at the problem and key options from vendors in the market today. Dremio is a new approach that eliminates the need for stand alone data prep tools.
During this webinar, we will review best practices and lessons learned from working with large and mid-size companies on their deployment of PostgreSQL. We will explore the practices that helped industry leaders move through these stages quickly, and get as much value out of PostgreSQL as possible without incurring undue risk.
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.
Gary Carter, Director of Product Marketing presents the accelerating adoption of Postgres by large organizations interested in reducing their database costs.
He reviews the main drivers of Postgres adoption, as well as the profiles of several organizations currently reaping the benefits of Postgres, and explore a few strategies that your organization can leverage to make the move at your pace – quickly or slowly.
To see the Webcast recording – please visit EnterpriseDB > Resources > Webcasts. Questions? Contact sales@enterprisedb.com
Introduction to Big Data and NoSQL.
This presentation was given to the Master DBA course at John Bryce Education in Israel.
Work is based on presentations by Michael Naumov, Baruch Osoveskiy, Bill Graham and Ronen Fidel.
Las nuevas arquitecturas, servicios y micro-servicios web, aplicaciones y apps, Bots, IoT, AI, etc., que demandan las organizaciones, necesitan cada vez más del talento y experiencia de los Administradores de Bases de Datos para dar consejos, sugerencias y respuestas que aporten un valor diferencial a los grupos de desarrollo y usuarios de negocio.
Te mostramos las claves del nuevo rol del DBA, que complementa la “A” de Administrar con: Analizar, Aconsejar, Automatizar y crear Arquitecturas eficientes y Autónomas para la gestión Avanzada de datos, colaborando con los desarrolladores y usuarios desde un conocimiento profundo de las base de datos.
Is Dynamic Cubes now ready to replace Transformer implementations? The business analytics experts at Senturus take an unbiased look at the pros and cons of switching. View the webinar video recording and download this deck: http://www.senturus.com/resources/cognos-dynamic-cubes-set-to-retire-transformer/.
Topics discussed include the types of Transformer implementations that could benefit by switching to Dynamic Cubes, pre-requisites for replacing a Transformer implementation with Dynamic Cubes and typical pitfalls you may encounter in the process.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
ADV Slides: When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
During this webinar, we will review best practices and lessons learned from working with large and mid-size companies on their deployment of PostgreSQL. We will explore the practices that helped industry leaders move through these stages quickly, and get as much value out of PostgreSQL as possible without incurring undue risk.
We have identified a set of levers that companies can use to accelerate their success with PostgreSQL:
- Application Tiering
- Collaboration between DBAs and Development Teams
- Evangelizing
- Standardization and Automation
- Balance of Migration and New Development
Recent advances in Postgres have propelled the database forward to meet today’s data challenges. At some of the world’s largest companies, Postgres plays a major role in controlling costs and reducing dependence on traditional providers.
This presentation addresses:
* What workloads are best suited for introducing Postgres into your environment
* The success milestones for evaluating the ‘when and how’ of expanding Postgres deployments
* Key advances in recent Postgres releases that support new data types and evolving data challenges
This presentation is intended for strategic IT and Business Decision-Makers involved in data infrastructure decisions and cost-savings.
Power BI Gateway: Understanding, Installing, ConfiguringSenturus
Learn how to use the Power BI gateway as a bridge between your on-premises data and your Microsoft cloud tools. Find out what the Power BI gateway is and how it works, how to install it on a local machine, and how to configure your Power BI service to use the gateway. See the recording and download this deck: https://senturus.com/resources/installing-configuring-power-bi-gateway/
Senturus offers a full spectrum of services for business analytics. Our Knowledge Center has hundreds of free live and recorded webinars, blog posts, demos and unbiased product reviews available on our website at: https://senturus.com/resources/
Learn how to improve the performance of your Cognos environment. We cover hardware and server specifics, architecture setup, dispatcher tuning, report specific tuning including the Interactive Performance Assistant and more. See the recording and download this deck: https://senturus.com/resources/cognos-analytics-performance-tuning/
Senturus offers a full spectrum of services for business analytics. Our Knowledge Center has hundreds of free live and recorded webinars, blog posts, demos and unbiased product reviews available on our website at: https://senturus.com/resources/
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http://spr.ly/BI41_Migration_Webinars - Learn how to develop a good strategy for sizing your SAP BusinessObjects BI 4.1 deployment. Understand why core architectural differences between former BOE XI releases and BI 4.1 mandate new sizing considerations. Find out how to test and tune your BI system before releasing it to your user base. Also, learn about virtualization support and guidelines when deploying to virtual and cloud environments.
• Understand how and where virtualization works well
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• Develop a strategy that allows for growth, and talk the same language as your administrators
For more on upgrading to SAP BusinessObjects BI 4.1, visit http://www.sapbusinessobjectsbi.com
IBM Cognos Analytics Release 7+ Authoring Improvements: Demos of New and Rein...Senturus
Add interactivity to reports with OLAP data, create briefing book-style reports based on existing reports using report references and tables of contents, use the report pages framework to combine presentations into a single report and increase efficiency in report building. View the video recording and download this deck at: http://www.senturus.com/resources/cool-improvements-for-report-developers-in-cognos-analytics-r7/.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Options for Data Prep - A Survey of the Current MarketDremio Corporation
Data comes in many shapes and sizes, and every company struggles to find ways to transform, validate, and enrich data for multiple purposes. The problem has been around as long as data, and the market has an overwhelming number of options. In this presentation we look at the problem and key options from vendors in the market today. Dremio is a new approach that eliminates the need for stand alone data prep tools.
During this webinar, we will review best practices and lessons learned from working with large and mid-size companies on their deployment of PostgreSQL. We will explore the practices that helped industry leaders move through these stages quickly, and get as much value out of PostgreSQL as possible without incurring undue risk.
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.
Gary Carter, Director of Product Marketing presents the accelerating adoption of Postgres by large organizations interested in reducing their database costs.
He reviews the main drivers of Postgres adoption, as well as the profiles of several organizations currently reaping the benefits of Postgres, and explore a few strategies that your organization can leverage to make the move at your pace – quickly or slowly.
To see the Webcast recording – please visit EnterpriseDB > Resources > Webcasts. Questions? Contact sales@enterprisedb.com
Introduction to Big Data and NoSQL.
This presentation was given to the Master DBA course at John Bryce Education in Israel.
Work is based on presentations by Michael Naumov, Baruch Osoveskiy, Bill Graham and Ronen Fidel.
Las nuevas arquitecturas, servicios y micro-servicios web, aplicaciones y apps, Bots, IoT, AI, etc., que demandan las organizaciones, necesitan cada vez más del talento y experiencia de los Administradores de Bases de Datos para dar consejos, sugerencias y respuestas que aporten un valor diferencial a los grupos de desarrollo y usuarios de negocio.
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Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
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Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
During this webinar, we will review best practices and lessons learned from working with large and mid-size companies on their deployment of PostgreSQL. We will explore the practices that helped industry leaders move through these stages quickly, and get as much value out of PostgreSQL as possible without incurring undue risk.
We have identified a set of levers that companies can use to accelerate their success with PostgreSQL:
- Application Tiering
- Collaboration between DBAs and Development Teams
- Evangelizing
- Standardization and Automation
- Balance of Migration and New Development
Recent advances in Postgres have propelled the database forward to meet today’s data challenges. At some of the world’s largest companies, Postgres plays a major role in controlling costs and reducing dependence on traditional providers.
This presentation addresses:
* What workloads are best suited for introducing Postgres into your environment
* The success milestones for evaluating the ‘when and how’ of expanding Postgres deployments
* Key advances in recent Postgres releases that support new data types and evolving data challenges
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Senturus offers a full spectrum of services across the BI stack plus training on Power BI, Cognos and Tableau. Our resource library has hundreds of free live and recorded webinars, blog posts, demos and unbiased product reviews available on our website at: http://www.senturus.com/senturus-resources/.
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Learn the complexities and unique aspects of the two leading cloud-based data warehouse contenders that are most likely tugging at your heartstrings: Snowflake Data Cloud and Azure Synapse Analytics.
Deciding on one is a long-term commitment. Before you put on ring on it, watch the recording to see demos of each data cloud, learn similarities, strengths and weaknesses of each and get criteria to help determine which is the right choice for your organization. View our on-demand webinar and download this deck at: https://senturus.com/resources/azure-synapse-vs-snowflake-price-performance/
Senturus offers a full spectrum of services across the BI stack plus training on Power BI, Cognos and Tableau. Our resource library has hundreds of free live and recorded webinars, blog posts, demos and unbiased product reviews available on our website at: http://www.senturus.com/senturus-resources/.
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Learn how BI teams build great reports consistently. We discuss how to improve report-building workflow and delivery rate while reducing mistakes. View our on-demand webinar and download this deck at: https://senturus.com/resources/secrets-of-high-performing-report-development-teams/.
Senturus offers a full spectrum of services across the BI stack plus training on Power BI, Cognos and Tableau. Our resource library has hundreds of free live and recorded webinars, blog posts, demos and unbiased product reviews available on our website at: http://www.senturus.com/senturus-resources/.
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Learn how to transform data into a format that aligns with the metrics you need. Power BI data cleansing technique demos include removing null values, removing columns, unpivoting data, add custom columns, merging queries and working with an M script. Watch the demos and download this deck at: https://senturus.com/resources/power-bi-data-cleansing-power-query-editor/
Senturus offers a full spectrum of services across the BI stack plus training on Power BI, Cognos and Tableau. Our resource library has hundreds of free live and recorded webinars, blog posts, demos and unbiased product reviews available on our website at: http://www.senturus.com/senturus-resources/.
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You can see the future first in San Francisco.
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The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
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Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
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Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
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Enhanced Enterprise Intelligence with your personal AI Data Copilot.pdfGetInData
Recently we have observed the rise of open-source Large Language Models (LLMs) that are community-driven or developed by the AI market leaders, such as Meta (Llama3), Databricks (DBRX) and Snowflake (Arctic). On the other hand, there is a growth in interest in specialized, carefully fine-tuned yet relatively small models that can efficiently assist programmers in day-to-day tasks. Finally, Retrieval-Augmented Generation (RAG) architectures have gained a lot of traction as the preferred approach for LLMs context and prompt augmentation for building conversational SQL data copilots, code copilots and chatbots.
In this presentation, we will show how we built upon these three concepts a robust Data Copilot that can help to democratize access to company data assets and boost performance of everyone working with data platforms.
Why do we need yet another (open-source ) Copilot?
How can we build one?
Architecture and evaluation
2. • Introductions
• OLAP Defined
• Why OLAP - Pros/Cons
• Current State of OLAP Architectures
• New Visualization Tools
• Fast Columnar/In-Memory Databases
• Big OLAP on Big Data
• Senturus Overview
• Additional Resources
Agenda
Copyright 2017 Senturus, Inc. All Rights Reserved.
3. Presenters
Copyright 2017 Senturus, Inc. All Rights Reserved.
Pedro Ining
Senior BI Architect
Senturus, Inc.
Jim Frazier
VP of Client Services
Senturus, Inc.
4. Hundreds of Free Resources
http://www.senturus.com/resources/
RESOURCE LIBRARY
An extensive, free library of past
webinars, demonstrations,
whitepapers, presentations, helpful hints,
and more.
Copyright 2017 Senturus, Inc. All Rights Reserved.
5. This slide deck is from the webinar
Is OLAP Dead?
To view the FREE video recording and download this
deck, go to:
http://www.senturus.com/resources/is-olap-dead/
Hear the Recording
Copyright 2017 Senturus, Inc. All Rights Reserved.
6. Is OLAP Dead?
Quotes on the state of OLAP Cubes
• ”In-memory databases are killing OLAP.”
• “The OLAP cube is history.”
• “Is OLAP still relevant?”
• “Building cubes for Tableau can be a waste of
time!”
Copyright 2017 Senturus, Inc. All Rights Reserved.
8. OLTP – Online Transaction Processing
• Core data repository of data flowing into business systems (ERP)
• Optimized for quick data entry and relational integrity
• Not optimized for reporting and data analysis
• Typically very complex schema design with many normalized
tables that facilitate high volume throughput of transactions
DWH - Data Warehouse
• Central repository of multiple ERP systems or other data sources
• The data warehouse (DWH) is a database system separate from
the OLTP
• Architected in an optimized fashion for easy reporting and
analysis
• Organizes and hides the complexity of the OLTP systems for
efficient, timely and accurate reporting
OLAP, OLTP, DWH Defined
Copyright 2017 Senturus, Inc. All Rights Reserved.
9. OLAP – Online Analytical Processing
• Edgar F. Codd ‘father of relational database’
coined the term OLAP, Arbor/Essbase went on to
market the term
• The data warehouse plus a central repository that
defines the relationships between tables
(facts/dimensions) and stores complex business
rules/calculations (e.g. YTD, YTD LY, Margins,
Inventory Turns, etc.)
• Allows for high performing interactive analysis
• Generally referred to as ‘cubes’
OLAP, OLTP, DWH Defined
Copyright 2017 Senturus, Inc. All Rights Reserved.
10. Data Repository
BI Tools
SourceSystemsofRecord
MetadataLayer
Information Security
Standard
Report
Authoring
KPI
Reports
Slicing and
Dicing
Threshold
Alerting
ERP
Data
CRM
Data
Other
SaaS
Sources
StandardETLSelf-ServiceETL/ELT
Standard
Reports
Dashboards/
Scorecards
Self-Service
Reporting &
Analysis
Threshold-
based Alerts
WebPortal
Star Schema
Conforming
Dimensional Models*
Data Lake
Data Hub/Hadoop
IOT
Data
Dashboard
Authoring
CloudSourceSystems
Click
Data
Pixel-Perfect
Copyright 2017 Senturus, Inc. All Rights Reserved.
Modern BI Architecture
11. BI Tools
OLAP
Layer
Properly Staged Data
Typical Best Practices BI System with OLAP Layer
Copyright 2017 Senturus, Inc. All Rights Reserved.
* Also known as a Star Schema
Conforming
Business Process
Dimensional Models*
Information Security
Standard
Reports
Dashboards/
Scorecards
Self-Service
Reporting &
Analysis
Threshold-
based Alerts
Architected Data Warehouse & BI Tools
Single Version of the Truth
DataAbstraction
Model
Report
Authoring
Dashboard
Authoring
Slicing &
Dicing
Ad Hoc
Querying
Threshold
Alerting
WebPortalorDesktopVizTools
12. • Historically, size and speed limitations of databases limited
query performance
• Cubes generally have higher performance vs. relational queries
• Central repository for relationships and complex business
calculations
• Buffers the business user from complex native database
structures and sensitive calculation logic
• Fast, simple, drag-and-drop ad-hoc analysis and reporting
⁃ Self-Service with guardrails
• Visual exploration
– Multi-dimensional view of data
– Drill-down on hierarchies
• Many business users love the interface and are used to querying
by governed data dimensions and measures that are prebuilt for
them
Why OLAP
Copyright 2017 Senturus, Inc. All Rights Reserved.
13. OLAP Familiar Interfaces
Excel on SSAS Tabular
Pre-Defined
Calculations
Visual display of
members &
hierarchies
Drag & Drop
Interfaces
Drill-Down
Tableau and Cubes
Copyright 2017 Senturus, Inc. All Rights Reserved.
14. Why Not OLAP
• Massive increase in data volumes
– Latency – large cubes increase cube build times, impacting SLAs
– Large cardinality dimensions and many dimensions
– Real-time updates are difficult if not impossible
• Movement of data into another proprietary structure
• Upfront investment in cube modeling
– Measures, dimensions, hierarchies all defined upfront
– Not a flexible agile BI environment
– Business process changes may require new cube designs.
• Continued developer maintenance and administration
• CPU power, memory and powerful servers are very
affordable – do we still need the OLAP layer
Copyright 2017 Senturus, Inc. All Rights Reserved.
15. To view the FREE video recording and download this
deck, go to:
http://www.senturus.com/resources/is-olap-dead/
The Senturus comprehensive library of recorded
webinars, demos, white papers, presentations and case
studies is available on our website:
http://www.senturus.com/resources/
Hear the Recording
Copyright 2017 Senturus, Inc. All Rights Reserved.
17. 17
MOLAP – Multi Dimension OLAP
• Most traditional OLAP design
• Data is stored in the multidimensional cube
• Data is moved from the relational database to the cube
• Data is pre-aggregated and allows for very fast analysis
ROLAP – Relational OLAP
• Modeled on top of the relational star schema database
• Data storage is kept in the relational database
• Utilizes SQL to query the DB in an OLAP manner
• May use proprietary in-memory caching techniques
HOLAP – Hybrid OLAP
• Combines the advantages of MOLAP and ROLAP
• Stores summary data in MOLAP structure
• Can ”drill-through” to relational database for more detail
Copyright 2017 Senturus, Inc. All Rights Reserved.
Traditional OLAP Architectures
18. For Dimensional BI Uses
• IBM Cognos Transformer Cubes (MOLAP)
• Microsoft SQL Server Analysis Services (SSAS)
– Dimensional and Tabular (MOLAP/HOLAP)
• IBM Cognos Dynamic Cubes (ROLAP)
• MicroStrategy (ROLAP)
Typically For Finance Use
• IBM Cognos TM1 (writeback and in-memory)
• Hyperion Essbase (writeback)
Top OLAP Products
Copyright 2017 Senturus, Inc. All Rights Reserved.
19. Advantages
• Performance (vs. relational)
• Easy to use and develop
• ETL-like capabilities (limited) – i.e. no star schema needed
• Can act as meta-data layer
• Great relative-time calc capabilities (YTD, Rolling 13 months)
• Less intensive hardware requirement
Challenges
• Significant cube size limitations
• Limited categories per dimension level
• Cube builds take time and cubes exist as separate files (.mdc)
• Lacks capabilities now available in other OLAP tools
• Row-level (dimensional) security is very challenging to maintain
• Unclear product support going forward
• Only works in the IBM Cognos stack
19
Copyright 2017 Senturus, Inc. All Rights Reserved.
Cognos PowerPlay (Transformer)
20. • The last significant update to Dynamic Cubes occurred
in version 10.2.2; IBM has since focused most
development efforts on the Cognos Analytics v11
release
• Currently, no current plans by IBM to enhance the
Dynamic Cubes product
20Copyright 2017 Senturus, Inc. All Rights Reserved.
• IBM Cognos Dynamic Cubes was added
to the Cognos 10.2 BI suite as an in-
memory relational OLAP product that
could address the challenge of high-
performance/low latency interactive
analysis against terabytes of data
IBM Cognos Dynamic Cubes
21. Advantages
• Scalability – limited only by database and RAM cache sizing
• Handles large dimensions well, allows dimension attributes
• Built-in relative time calcs on par with Transformer
• MDX Scripting – can set up just about any type of calculation
• Dynamic security – can set up dimensional filtering so that all security is
derived from SQL tables
• Aggregate aware – can dynamically select database aggregate tables or in-
memory aggregates for fast results
21
Challenges
• Requires star or snowflake schema as data source
• Cache needs to be warmed for decent performance
• Requires 64-bit application server and may require significant memory
footprint for large cubes (e.g. 64-128GB)
• Report authors require dimensional reporting experience
• CAN ONLY BE USED BY COGNOS BI STACK (Senturus has developed
the Analytics Connector to access Tableau)
Copyright 2017 Senturus, Inc. All Rights Reserved.
IBM Cognos Dynamic Cubes
22. • Finance project used IBM Cognos
Dynamic Cubes to replace legacy
Cognos Transformer cubes, went
into production Q1 2017
• Large number of reports were
converted or created on top of the
Dynamic Cube to provide a guided
set of highly formatted reports that
allowed drill-down
• Many complex business calculations
were developed and stored in the
cube, report writers can leverage a
central set of calculations without
having to write them in the report
Dynamic Cubes in Play
Large Health Insurance Provider Deployed Dynamic Cubes
Copyright 2017 Senturus, Inc. All Rights Reserved.
23. 23
Multi-Dimensional Tabular
Dimensions and Measure Groups Tables and Relationships
Highly Scalable and Mature Fast Design and In-Memory
Feature Rich and Complex Easy to Get Started
Copyright 2017 Senturus, Inc. All Rights Reserved.
Microsoft SQL Server Analysis Services (SSAS)
24. • Introduced in SQL Server 2012
• Model paradigm = tables and
relationships
• Data stored in-memory
• Uses a different engine (xVelocity) and
uses a columnar DB structure
• Combines the functionality of MOLAP
cubes and relational DBs
24
Copyright 2017 Senturus, Inc. All Rights Reserved.
Microsoft SQL Server Analysis Services (SSAS)
Tabular Model
25. Advantages
• Simpler data development model, faster to
develop
• Generally much faster than MOLAP
• DAX learning curve is easier than MDX
• Fast COUNT DISTINCT queries
Challenges
• Dependent on server memory footprint (DirectQuery
mode available in 2016)
• Some multidimensional features are not available (e.g.
many-to-many)
• Complex calculations may be difficult to implement
• Large datasets
25
Copyright 2017 Senturus, Inc. All Rights Reserved.
Microsoft SQL Server Analysis Services (SSAS)
Tabular Model
26. • Re-architected an older Oracle based data
warehouse to a SQL Server
• User community already very familiar with cube
technologies
• Wanted to use SSAS OLAP cubes for their advanced
relative time calcs
• Ability to create complicated advanced inventory
calcs and on the fly currency conversions
• Ability to set defaults for certain dimensions such as
currency type
• SSAS fits into their corporate strategy for multiple
tools
• SSAS Tabular was chosen for performance and
flexibility
SSAS in Play
Major American Clothing Company
Copyright 2017 Senturus, Inc. All Rights Reserved.
27. To view the FREE video recording and download this
deck, go to:
http://www.senturus.com/resources/is-olap-dead/
The Senturus comprehensive library of recorded
webinars, demos, white papers, presentations and case
studies is available on our website:
http://www.senturus.com/resources/
Hear the Recording
Copyright 2017 Senturus, Inc. All Rights Reserved.
29. • Over the last few years desktop visualization
tools have sprouted on desktops throughout the
enterprise
• IBM Cognos Analytics v11 allows similar
functionality over a web interface
• Rich visualizations are easily created by business
users without the help of IT
• Decentralized model of data governance
• No waiting on developers to create next iteration
of an OLAP cube
• Allows users to integrate data on the
desktop/web
• Creation of desktop ‘micromodels’ (Tableau data
extracts)
• Can use OLAP datasources, but works best with
non-OLAP sources
• Can begin to have performance issues when
creating large data extracts or going against
large datasources
New Generation Visualization Tools
Copyright 2017 Senturus, Inc. All Rights Reserved.
30. OLAP concepts like dimensions and hierarchies are alive and well in Tableau
Tableau
Copyright 2017 Senturus, Inc. All Rights Reserved.
Dimensions
Hierarchies
31. • TDE is a compressed snapshot of data stored on disk and loaded
into memory as required
• Data engine can be described as its own “in-memory analytic
database”
• Stores data in a columnar store structure
• Dramatically reduces the input/output time required to access and
aggregate values
• New in upcoming 10.5 – hyper data engine
Reasons to Use TDEs
• Better performance vs. connected data sources
• Reduced load on connected data sources
• Portability – can be bundled in a packaged workbook for easy
sharing
• Pre-aggregation – option to aggregate data for visible dimensions
“aggregated extract”
Tableau Data Extracts
“Building Cubes for Tableau can be a waste of time!”
Copyright 2017 Senturus, Inc. All Rights Reserved.
32. • Leverages
– One version of the truth
– Complex calcs that are already created in the cube
– Billions of rows response time across pre-aggregated calcs - faster
• Tableau will work if you stay within the structure of the cube
• Functional differences
– No cube extracts (10.4 supports BW cubes)
– No user-defined hierarchies
– Aggregations controlled in the cube
• Supports
– Oracle Hyperion Essbase
– Teradata OLAP
– Microsoft Analysis Services (SSAS)
– SAP NetWeaver Business Warehouse
– Microsoft PowerPivot
– Analytical Views in SAP Hana
Tableau and Cubes
“But wait Tableau does support cubes.”
Copyright 2017 Senturus, Inc. All Rights Reserved.
33. • Cognos Analytics v11 architecture adds data modules
which represent a major shift in the central
metadata layer (framework) paradigm
• Data modules allows end users to quickly add new
data sources and model new data subjects without
having to wait for DWH changes
• Uploaded files and data sources can be stored as
‘snapshots’ on the server’s file system using the
Apache Parquet columnar file storage mechanism
• Allows for fast query response times
IBM Cognos Analytics v11
Copyright 2017 Senturus, Inc. All Rights Reserved.
35. 35
Will optimizing the
database with columnar
and in-memory
technologies remove the
need for OLAP cubes?
Copyright 2017 Senturus, Inc. All Rights Reserved.
In-Memory Databases Are Killing OLAP
36. Columnar Databases
• Traditional databases store data by each row
• Columnar databases store data in columns rather than in rows
• This storage architecture can result in high-performing queries especially
aggregation queries
• Example DBS:
⁃ Sybase IQ
⁃ IBM DB2 with BLU Acceleration
• A capability built into DB2, not a separate install component
• Focus on analytics
• Dynamic in-memory, does not require all data to be in-memory
• Columnar and traditional row-based tables
• SQL Server 2014/16
• Columnar store indexes
• In-memory OLTP tables
36
Copyright 2017 Senturus, Inc. All Rights Reserved.
Columnar & In-Memory Databases
37. • Raw queries will be fast, but what about the semantic
layer?
• You could use relational models with some level of
metadata and calculations
• But complex calcs, dimensions, drill downs would be
missing
37
Copyright 2017 Senturus, Inc. All Rights Reserved.
But If Remove the OLAP Layer
38. The New School Big OLAP on Big Data
THE CURRENT STATE OF OLAP
ARCHITECTURE
39. Several new vendors and open source solutions are
creating new scalable OLAP on Hadoop products
Big OLAP on Big Data
Copyright 2017 Senturus, Inc. All Rights Reserved.
40. • Slow performing queries on big data
implementations are driving new OLAP technologies
• Classic OLAP technologies on big data necessitated
movement of Hadoop data into traditional relational
data warehouses further increasing latency
• New OLAP technologies are architected to be part of
the Hadoop stack and allow queries across Hadoop
with no additional movement of data
Big OLAP on Big Data
Copyright 2017 Senturus, Inc. All Rights Reserved.
41. Big OLAP on Big Data
Copyright 2017 Senturus, Inc. All Rights Reserved.
43. • In general, the key concepts of OLAP – dimensions,
measures, hierarchies, drill-down are still alive and
well but the technology that surfaces those concepts
are changing
• Business users will always want a high performing BI
layer that is easy to use and allows for interactive BI
• Some will want a central repository that contains all
the relationships, hierarchies and complex business
rules already developed
• Other users like data scientists and advanced
business analysts will want a more agile free form
solution with have high performance
So Is OLAP Dead?
Copyright 2017 Senturus, Inc. All Rights Reserved.
44. BI Architectural Guidance
Copyright 2017 Senturus, Inc. All Rights Reserved.
• Best practices
• Pragmatic recommendations
• Path to an architecture that supports current needs
and grows for future
Consultation with Senturus Senior BI Architect
at special prices for webinar attendees
20 hours $3799 40 hours $7399
45. To view the FREE video recording and download this
deck, go to:
http://www.senturus.com/resources/is-olap-dead/
The Senturus comprehensive library of recorded
webinars, demos, white papers, presentations and case
studies is available on our website:
http://www.senturus.com/resources/
Hear the Recording
Copyright 2017 Senturus, Inc. All Rights Reserved.
47. Bridging the Gap Between Data & Decision Making
Analysis
Ready
Data
DECISIONS
& ACTIONS
Business Needs
Analysis
Ready
Data
Copyright 2017 Senturus, Inc. All Rights Reserved.
48. • Dashboards, Reporting & Visualizations
• Data Preparation & Modern Data Warehousing
• Self-Service Business Analytics
• Big Data & Advanced Analytics
• Planning & Forecasting Systems
• Proprietary Analytics Connector
Software
Business Analytics Architects
Copyright 2017 Senturus, Inc. All Rights Reserved.
49. 1000+ Clients, 2000+ Projects, 17+ Years
Copyright 2017 Senturus, Inc. All Rights Reserved.
53. *Custom, tailored training also available*
Cognos & Tableau Training Options
Copyright 2017 Senturus, Inc. All Rights Reserved.
54. Thank You!
www.senturus.com
info@senturus.com
888 601 6010
Copyright 2017 by Senturus, Inc.
This entire presentation is copyrighted and may not be
reused or distributed without the written consent of
Senturus, Inc.
Copyright 2017 Senturus, Inc. All Rights Reserved.