Why NoSQL Makes Sense

•

0 likes•539 views

Former DoubleClick Founder and CTO Dwight Merriman wrote the first lines of MongoDB code in 2007. He drew upon his experiences building large scale, high availability, robust systems to create a new kind of database. This session will introduce some of the background to how and why MongoDB came about to address the need for a more scalable database, and provide some key use cases and rationale for a new product category in the database marketplace.

Technology Education

Why NoSQL Makes Sense
Why NoSQL Makes Sense

NoSQL Now
Dwight Merriman / 10gen
Dwight Merriman / 10gen

signs we needed something different
signs we needed something different

• doubleclick ‐ 400,000 ads/second
• people writing their own stores
people writing their own stores
• caching is de rigueur
• complex ORM frameworks
• computer architecture trends
p
• cloud computing

the db space 2000
the db space 2000 ‐ 2010
+ great for complex
dh i
+ ad hoc queries easy transactions
+ SQL gives us a standard + great for tabular data
protocol for the interface + ad hoc queries easy
between clients and ‐ O<‐>R mapping hard
servers ‐ speed/scale challenges
+ scales horizontally ‐ not super agile
better than operational
dbs. some scale limits at BI / OLTP /
massive scale
i l reporting
i operational
i l
‐ schemas are rigid
‐ real time is hard; very
good at bulk nightly data
loads

the db space
the db space
+ fits OO programming
wellll
+ agile
+ speed/scale
‐ querying a little less
scalable
l bl add hoc
dd h
nonrelational ‐ not super transactional
BI / reporting (“nosql”) ‐ not sql

OLTP /
OLTP /
operational

as simple as possible
but no simpler
b l

as simple as possible
but no simpler
b l
• need a good degree of functionality to handle
a large set of use cases
– sometimes need strong consistency / atomicity
– secondary indexes
– ad hoc queries

as simple as possible
but no simpler
b l
• but, leave out a few things so we can scale
– no choice but to leave out relational
– distributed transactions are hard to scale

as simple as possible
but no simpler
b l
• to scale, need a new data model. some
options:
– key/value
– columnar / tabular
– document oriented (JSON inspired)
• opportunity to innovate ‐> agility
pp y g y

mongodb philosphy
mongodb philosphy
• No longer one‐size‐fits all. but not 12 tools either.
N l i fit ll b t t 12 t l ith
• By reducing transactional semantics the db provides, one can still solve an
interesting set of problems where performance is very important, and
horizontal scaling then becomes easier.
hori ontal scaling then becomes easier
• Non‐relational (no joins) makes scaling horizontally practical
• Document data models are good
• Keep functionality when we can (key/value stores are great, but we nee
more)
• Database technology should run anywhere, being available both for
running on your own servers or VMs, and also as a cloud pay‐for‐what‐
you‐use service. And ideally open source...

Questions?

http://blog.mongodb.org/
@mongodb
me
me ‐ @dmerr

www.mongodb.org
http://groups.google.com/group/mongodb‐user
htt // l / / db
irc://irc.freenode.net/#mongodb

thanks

What's hot

L20 Scalability

Ólafur Andri Ragnarsson

Hadoop World 2011: Apache HBase Road Map - Jonathan Gray - Facebook

Cloudera, Inc.

Big Data Journey

Tugdual Grall

Getting Started with NuoDB Community Edition

NuoDB

Adobe Systems uses “SaasBase Analytics” to incrementally process large heterogeneous data sets into pre-aggregated, indexed views, stored in HBase to be queried in real- time. Our goal was to process new data in real- time (currently minutes) and have it ready for a large number of concurrent queries that execute in milliseconds. This set our problem apart from what is traditionally solved with Hive or PIG. In this talk I’ll describe the design and the strategies (and hacks) we used to achieve low latency and scalability, from theoretical model to the entire process of ETL to warehousing and queries.

HBaseCon 2012 | Low Latency OLAP with HBase - Cosmin Lehene, Adobe

Cloudera, Inc.

BDM37: Hadoop in production – the war stories by Nikolaï Grigoriev, Principal...

Big Data Montreal

TriHUG - Beyond Batch

boorad

Oracle Migration to Postgres in the Cloud

EDB

Design, Scale and Performance of MapR's Distribution for Hadoop

mcsrivas

SimplifyStreamingArchitecture

Maheedhar Gunturu

The Future of Hadoop: MapR VP of Product Management, Tomer Shiran

MapR Technologies

D3 d12 a-new-meaning-for-efficiency-and-performance

mistercteam

North Bay Ruby Meetup 101911

Ines Sombra

MongoDB at eBay

MongoDB

What's hot (14)

L20 Scalability

Hadoop World 2011: Apache HBase Road Map - Jonathan Gray - Facebook

Big Data Journey

Getting Started with NuoDB Community Edition

HBaseCon 2012 | Low Latency OLAP with HBase - Cosmin Lehene, Adobe

BDM37: Hadoop in production – the war stories by Nikolaï Grigoriev, Principal...

TriHUG - Beyond Batch

Oracle Migration to Postgres in the Cloud

Design, Scale and Performance of MapR's Distribution for Hadoop

SimplifyStreamingArchitecture

The Future of Hadoop: MapR VP of Product Management, Tomer Shiran

D3 d12 a-new-meaning-for-efficiency-and-performance

North Bay Ruby Meetup 101911

MongoDB at eBay

Similar to Why NoSQL Makes Sense

Why mongo db was created - Dwight Merriman - MongoSF 2011

MongoDB

Intro to NoSQL and MongoDB

DATAVERSITY

Processing Big Data

cwensel

Seattle Scalability Meetup - Ted Dunning - MapR

clive boulton

001 hbase introduction

Scott Miao

Next Generation Data Platforms - Deon Thomas

Thoughtworks

Взгляд на облака с точки зрения HPC

Olga Lavrentieva

Bank Data Frank Peterson DB2 10-Early_Experiences_pdf

Surekha Parekh

Mobile Development Meets Semantic Technology

Blue Slate Solutions

Drill njhug -19 feb2013

MapR Technologies

Historically, enterprises used traditional RDBMs for on-line transaction processing (OLTP) applications. We affectionately call these systems OldSQL, because they are largely legacy code bases, originally written decades ago. New OLTP applications have more extreme performance requirements than the Old OLTP applications of yesteryears. These are caused by web users directly submitting transactions rather than using a professional terminal operator and by mobile devices (and sensors) enabling transaction submission from many more locations. In a considerable number of modern applications (multiplayer games, risk analysis in electronic trading, gambling, social networks, etc.) OldSQL is cracking under the volume of interactions. This talk contrasts two alternatives to OldSQL in this area: NoSQL, where both SQL and ACID transactions are jettisoned for better performance NewSQL, where SQL and ACID are retained, and better performance is delivered through innovative architectures

NewSQL vs NoSQL for New OLTP

DATAVERSITY

NoSQL

dbulic

Track B-3 解構大數據架構 - 大數據系統的伺服器與網路資源規劃

Etu Solution

High Performance Computing - Cloud Point of View

aragozin

DevNation Atlanta

boorad

Hadoop for the Absolute Beginner

Ike Ellis

Big iron 2 (published)

Ben Stopford

Kb 40 kevin_klineukug_reading20070717[1]

shuwutong

Storing and processing data with the wso2 platform

WSO2

Microsoft Openness Mongo DB

Heriyadi Janwar

Similar to Why NoSQL Makes Sense (20)

Why mongo db was created - Dwight Merriman - MongoSF 2011

Intro to NoSQL and MongoDB

Processing Big Data

Seattle Scalability Meetup - Ted Dunning - MapR

001 hbase introduction

Next Generation Data Platforms - Deon Thomas

Взгляд на облака с точки зрения HPC

Bank Data Frank Peterson DB2 10-Early_Experiences_pdf

Mobile Development Meets Semantic Technology

Drill njhug -19 feb2013

NewSQL vs NoSQL for New OLTP

NoSQL

Track B-3 解構大數據架構 - 大數據系統的伺服器與網路資源規劃

High Performance Computing - Cloud Point of View

DevNation Atlanta

Hadoop for the Absolute Beginner

Big iron 2 (published)

Kb 40 kevin_klineukug_reading20070717[1]

Storing and processing data with the wso2 platform

Microsoft Openness Mongo DB

More from DATAVERSITY

Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a comprehensive platform designed to address multi-faceted needs by offering multi-function data management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion. In this research-based session, I’ll discuss what the components are in multiple modern enterprise analytics stacks (i.e., dedicated compute, storage, data integration, streaming, etc.) and focus on total cost of ownership. A complete machine learning infrastructure cost for the first modern use case at a midsize to large enterprise will be anywhere from $3 million to $22 million. Get this data point as you take the next steps on your journey into the highest spend and return item for most companies in the next several years.

Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...

DATAVERSITY

Do you ever wonder how data-driven organizations fuel analytics, improve customer experience, and accelerate business productivity? They are successful by governing and mastering data effectively so they can get trusted data to those who need it faster. Efficient data discovery, mastering and democratization is critical for swiftly linking accurate data with business consumers. When business teams can quickly and easily locate, interpret, trust, and apply data assets to support sound business judgment, it takes less time to see value. Join data mastering and data governance experts from Informatica—plus a real-world organization empowering trusted data for analytics—for a lively panel discussion. You’ll hear more about how a single cloud-native approach can help global businesses in any economy create more value—faster, more reliably, and with more confidence—by making data management and governance easier to implement.

Data at the Speed of Business with Data Mastering and Governance

DATAVERSITY

What is data literacy? Which organizations, and which workers in those organizations, need to be data-literate? There are seemingly hundreds of definitions of data literacy, along with almost as many opinions about how to achieve it. In a broader perspective, companies must consider whether data literacy is an isolated goal or one component of a broader learning strategy to address skill deficits. How does data literacy compare to other types of skills or “literacy” such as business acumen? This session will position data literacy in the context of other worker skills as a framework for understanding how and where it fits and how to advocate for its importance.

Exploring Levels of Data Literacy

DATAVERSITY

Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.

Building a Data Strategy – Practical Steps for Aligning with Business Goals

DATAVERSITY

Uncover how your business can save money and find new revenue streams. Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how? By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability. In this webinar, you'll learn: - How your company can leverage data and AI to reduce spending and costs - Ways you can monetize data and AI and uncover new growth strategies - How different companies have implemented these strategies to achieve cost optimization benefits

Make Data Work for You

DATAVERSITY

Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data. Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.

Data Catalogs Are the Answer – What is the Question?

DATAVERSITY

Data Catalogs Are the Answer – What Is the Question?

DATAVERSITY

Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: “Big Data,” “NoSQL,” “Data Scientist,” and so on. Few realize that all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, data modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important the data models driving the engineering and architecture activities of your organization. This webinar illustrates data modeling as a key activity upon which so much technology and business investment depends. Specific learning objectives include: - Understanding what types of challenges require data modeling to be part of the solution - How automation requires standardization on derivable via data modeling techniques - Why only a working partnership between data and the business can produce useful outcomes

Data Modeling Fundamentals

DATAVERSITY

Analytics play a critical role in supporting strategic business initiatives. Despite the obvious value to analytic professionals of providing the analytics for these initiatives, many executives question the economic return of analytics as well as data lakes, machine learning, master data management, and the like. Technology professionals need to calculate and present business value in terms business executives can understand. Unfortunately, most IT professionals lack the knowledge required to develop comprehensive cost-benefit analyses and return on investment (ROI) measurements. This session provides a framework to help technology professionals research, measure, and present the economic value of a proposed or existing analytics initiative, no matter the form that the business benefit arises. The session will provide practical advice about how to calculate ROI and the formulas, and how to collect the necessary information.

Showing ROI for Your Analytic Project

DATAVERSITY

Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls. This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture. Attend this session to learn about: - The role of a Data Mesh in the modern cloud architecture. - How a semantic layer can serve as the binding agent to support decentralization. - How to drive self service with consistency and control.

How a Semantic Layer Makes Data Mesh Work at Scale

DATAVERSITY

Enterprise data literacy. A worthy objective? Certainly! A realistic goal? That remains to be seen. As companies consider investing in data literacy education, questions arise about its value and purpose. While the destination – having a data-fluent workforce – is attractive, we wonder how (and if) we can get there. Kicking off this webinar series, we begin with a panel discussion to explore the landscape of literacy, including expert positions and results from focus groups: - why it matters, - what it means, - what gets in the way, - who needs it (and how much they need), - what companies believe it will accomplish. In this engaging discussion about literacy, we will set the stage for future webinars to answer specific questions and feature successful literacy efforts.

Is Enterprise Data Literacy Possible?

DATAVERSITY

Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent – not just react – to internal and external threats, and 3) comply with data privacy and security regulations. Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value. Join us for this panel discussion with experts in these fields as they discuss: - Recent research about where data privacy, security and governance stand - The most valuable enterprise data use cases - The common obstacles to data value creation - New approaches to data privacy, security and governance - Their advice on how to shift from a reactive to resilient mindset/culture/organization You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.

The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...

DATAVERSITY

Emerging Trends in Data Architecture – What’s the Next Big Thing?

DATAVERSITY

As DATAVERSITY’s RWDG series hurdles into our 12th year, this webinar takes a quick look behind us, evaluates the present, and predicts the future of Data Governance. Based on webinar numbers, hot Data Governance topics have evolved over the years from policies and best practices, roles and tools, data catalogs and frameworks, to supporting data mesh and fabric, artificial intelligence, virtualization, literacy, and metadata governance. Join Bob Seiner as he reflects on the past and what has and has not worked, while sharing examples of enterprise successes and struggles. In this webinar, Bob will challenge the audience to stay a step ahead by learning from the past and blazing a new trail into the future of Data Governance. In this webinar, Bob will focus on: - Data Governance’s past, present, and future - How trials and tribulations evolve to success - Leveraging lessons learned to improve productivity - The great Data Governance tool explosion - The future of Data Governance

Data Governance Trends - A Look Backwards and Forwards

DATAVERSITY

Would you share your bank account information on social media? How about shouting your social security number on the New York City subway? We didn’t think so either – that’s why data governance is consistently top of mind. In this webinar, we’ll discuss the common Cloud data governance best practices – and how to apply them today. Join us to uncover Google Cloud’s investment in data governance and learn practical and doable methods around key management and confidential computing. Hear real customer experiences and leave with insights that you can share with your team. Let’s get solving. Topics that you will hear addressed in this webinar: - Understanding the basics of Cloud Incident Response (IR) and anticipated data governance trends - Best practices for key management and apply data governance to your day-to-day - The next wave of Confidential Computing and how to get started, including a demo

Data Governance Trends and Best Practices To Implement Today

DATAVERSITY

It is a fascinating, explosive time for enterprise analytics. It is from the position of analytics leadership that the enterprise mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics. The coming years will be full of big changes in enterprise analytics and data architecture. William will kick off the fifth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.

2023 Trends in Enterprise Analytics

DATAVERSITY

Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following: - Your organization’s data - The way your people use data - The way your people use data to achieve your organizational strategy This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including: - A cohesive argument for why data strategy is necessary for effective data governance - An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls - A repeatable process for identifying and removing data constraints - The importance of balancing business operation and innovation

Data Strategy Best Practices

DATAVERSITY

The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question. Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more. In this session Bob will share: - What is meant by “the business” when it comes to owning Data Governance - Why some people say that Data Governance in IT is destined to fail - Examples of IT positioned Data Governance success - Considerations for answering the question in your organization - The final answer to the question of who should own Data Governance

Who Should Own Data Governance – IT or Business?

DATAVERSITY

It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This program describes what must be done at the programmatic level to achieve better data use and a way to implement this as part of your data program. The approach combines DMBoK content and CMMI/DMM processes – permitting organizations with the opportunity to benefit from the best of both. It also permits organizations to understand: - Their current Data Management practices - Strengths that should be leveraged - Remediation opportunities

Data Management Best Practices

DATAVERSITY

MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning” and “operations,” MLOps applies DevOps principles to ML delivery, enabling the delivery of ML-based innovation at scale to result in: Faster time to market of ML-based solutions More rapid rate of experimentation, driving innovation Assurance of quality, trustworthiness, and ethical AI MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.

MLOps – Applying DevOps to Competitive Advantage

DATAVERSITY

More from DATAVERSITY (20)

Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...

Data at the Speed of Business with Data Mastering and Governance

Exploring Levels of Data Literacy

Building a Data Strategy – Practical Steps for Aligning with Business Goals

Make Data Work for You

Data Catalogs Are the Answer – What is the Question?

Data Catalogs Are the Answer – What Is the Question?

Data Modeling Fundamentals

Showing ROI for Your Analytic Project

How a Semantic Layer Makes Data Mesh Work at Scale

Is Enterprise Data Literacy Possible?

The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...

Emerging Trends in Data Architecture – What’s the Next Big Thing?

Data Governance Trends - A Look Backwards and Forwards

Data Governance Trends and Best Practices To Implement Today

2023 Trends in Enterprise Analytics

Data Strategy Best Practices

Who Should Own Data Governance – IT or Business?

Data Management Best Practices

MLOps – Applying DevOps to Competitive Advantage

Recently uploaded

Explore the core of Salesforce success in 'Salesforce Adoption – Metrics, Methods, and Motivation.' We will discuss essential metrics, effective methods to drive adoption, and the driving force behind user engagement and explore strategies for onboarding, training, and continuous support that empower users to navigate the platform seamlessly. By leveraging these tools, you can effectively measure adoption against your company’s goals and create an environment where users not only adopt Salesforce but actively contribute to its ongoing success.

Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom

CzechDreamin

When stars align: studies in data quality, knowledge graphs, and machine lear...

Elena Simperl

The standard Salesforce Approval process can be limiting in many ways, especially in complex scenarios. What if there was a way to implement very flexible approvals where one can use Apex code to make data updates in unrelated records, dynamically generate next steps details, and compute assignees on the fly? And still use UI-based configurations to implement concrete approval processes. In this session, we will share ideas behind such a solution and show a few lines of code to get you started.

Custom Approval Process: A New Perspective, Pavel Hrbacek & Anindya Halder

CzechDreamin

De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...

Product School

ODC, Data Fabric and Architecture User Group

CatarinaPereira64715

Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place. Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects. Here’s what you’ll gain: - Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows. - Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy. - Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency. - Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity. We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic. Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.

Essentials of Automations: Optimizing FME Workflows with Parameters

Safe Software

From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...

Product School

UiPath Test Automation using UiPath Test Suite series, part 3

DianaGray10

In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring. Learn about: • The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks. • Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective. • Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification. • Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process. Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.

Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered Quality

Inflectra

Discover the essentials of performance testing in the IT sector with our concise guide. Learn about various testing types such as load, stress, endurance, spike, scalability, and volume testing. Understand key performance metrics like response time, throughput, CPU and memory utilization, and error rate. Explore top tools like Apache JMeter, LoadRunner, Gatling, Neoload, and BlazeMeter. Gain insights into best practices for defining objectives, creating realistic scenarios, automating tests, and optimizing performance to ensure user satisfaction, reliability, scalability, and cost efficiency. Ideal for developers, QA engineers, and IT professionals. Visit Expeed Software for more information. https://expeed.com/

In-Depth Performance Testing Guide for IT Professionals

Expeed Software

Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application. In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics. Length: 30 minutes Session Overview ------------------------------------------- During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana: - What out-of-the-box solutions are available for real-time monitoring JMeter tests? - What are the benefits of integrating InfluxDB and Grafana into the load testing stack? - Which features are provided by Grafana? - Demonstration of InfluxDB and Grafana using a practice web application To view the webinar recording, go to: https://www.rttsweb.com/jmeter-integration-webinar

JMeter webinar - integration with InfluxDB and Grafana

RTTS

This talk focuses on the practical aspects of integrating various telephony systems with Salesforce, drawing on examples from implementations in the Czech scene. It aims to inform attendees about the spectrum of telephony solutions available, from small to large scale, and their compatibility with Salesforce. The presentation will highlight key considerations for selecting a telephony provider that integrates smoothly with Salesforce, including important questions to support the decision-making process. It will also discuss methods for integrating existing telephony systems with Salesforce, aimed at companies contemplating or in the process of adopting this CRM platform. The discussion is designed to provide a straightforward overview of the steps and considerations involved in telephony and Salesforce integration, with an emphasis on functionality, compatibility, and the practical experiences of Czech companies.

Integrating Telephony Systems with Salesforce: Insights and Considerations, B...

CzechDreamin

Assuring Contact Center Experiences for Your Customers With ThousandEyes

ThousandEyes

Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...

Thierry Lestable

How to differentiate Sales Cloud and CPQ on first glance might be tricky if you do not know where to look and what to look at. You will know :-) Managing the sales process within Salesforce is a common use case that can be managed with standart Sales Cloud. If you want to do entire quoting process you will find out Salesforce CPQ solution exists. What is then the difference if both can handle selling products? You will see comparison of 10 different features, which Sales Cloud and Salesforce CPQ handle differently. Simple question you will always remember if you should consider using Salesforce CPQ will be a cherry on top.

10 Differences between Sales Cloud and CPQ, Blanka Doktorová

CzechDreamin

New customer? New industry? New cloud? New team? A lot to handle! How to ensure the success of the project? Start it well! I've created the 3 areas of focus at the beginning of the project that helped me in multiple roles (BA, PO, and Consultant). Learn from real-world experiences and discover how these insights can empower you to deliver unparalleled value to your customers right from the project's start.

Powerful Start- the Key to Project Success, Barbara Laskowska

CzechDreamin

I'm excited to share my latest predictions on how AI, robotics, and other technological advancements will reshape industries in the coming years. The slides explore the exponential growth of computational power, the future of AI and robotics, and their profound impact on various sectors. Why this matters: The success of new products and investments hinges on precise timing and foresight into emerging categories. This deck equips founders, VCs, and industry leaders with insights to align future products with upcoming tech developments. These insights enhance the ability to forecast industry trends, improve market timing, and predict competitor actions. Highlights: ▪ Exponential Growth in Compute: How $1000 will soon buy the computational power of a human brain ▪ Scaling of AI Models: The journey towards beyond human-scale models and intelligent edge computing ▪ Transformative Technologies: From advanced robotics and brain interfaces to automated healthcare and beyond ▪ Future of Work: How automation will redefine jobs and economic structures by 2040 With so many predictions presented here, some will inevitably be wrong or mistimed, especially with potential external disruptions. For instance, a conflict in Taiwan could severely impact global semiconductor production, affecting compute costs and related advancements. Nonetheless, these slides are intended to guide intuition on future technological trends.

Future Visions: Predictions to Guide and Time Tech Innovation, Peter Udo Diehl

Peter Udo Diehl

The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.

Search and Society: Reimagining Information Access for Radical Futures

Bhaskar Mitra

Already know how to write a basic SOQL query? Great! But what about an *aggregate* SOQL query? You know, the kind that uses aggregate functions like COUNT & MAX along with GROUP BY and HAVING clauses? No? Well, get ready to learn how to slice & dice your org’s data right inside your own dev console. From finding duplicate records to prototyping summary & matrix reports, learn the ins and outs of aggregate queries during this fast-paced but admin-friendly session on advanced SOQL concepts.

SOQL 201 for Admins & Developers: Slice & Dice Your Org’s Data With Aggregate...

CzechDreamin

To Graph or Not to Graph Knowledge Graph Architectures and LLMs

Paul Groth

Recently uploaded (20)