This webinar will cover the latest trends in advanced query languages for NoSQL databases. We’ll look at how innovations in vendor-independent standardized query languages allow NoSQL developers to query multiple types of data and multiple NoSQL databases using a single query language. We’ll see how using the right NoSQL query language promotes portability across multiple NoSQL databases, avoids vendor lock-in, and keeps your developers productive at the same time. We will be interviewing Matthias Brantner from 28msec and see on how they use JSONiq as a basis for a modern ETL framework that works on a diverse number of data sources.
Если раньше при старте нового проекта нам нужно было выбрать одну из доступных на тот момент SQL баз данных, то за последние 5 лет ситуация кардинально изменилась. Теперь выбор стал гораздо сложнее. SQL или NoSQL? Сloud или on-premises? Если SQL/NoSQL - то какая именно? А может использовать и то и другое?
В данном докладе мы постараемся представить общий обзор доступных сегодня решений для хранения данных и определиться с критериями выбора.
Sebastian Cohnen – Building a Startup with NoSQL - NoSQL matters Barcelona 2014NoSQLmatters
Sebastian Cohnen – Building a Startup with NoSQL
At StormForger we use several NoSQL systems to handle all kinds of different data. We have a lot of time series data based on the fact, that we do load testing and performance analysis of HTTP-based infrastructure and services. For time series data, we use InfluxDB. We also use several Redis instances for caching and storing structured data, that needs to be fast on read and write access. Lately we also started to integrate ArangoDB into our architecture, which is a perfect fit for storing and working with our complex test case definition data structures. In this talk I’d like to present how we build our startup on the foundation provided by several NoSQL databases, how we came to choose those systems and how we use them.
SQL vs. NoSQL. It's always a hard choice.Denis Reznik
This will be an interesting and sometimes fun session with a small demo. This session will answer some of your questions and force you to think about new questions. It will not be very technical, so it's ok for choose another more technical session from the schedule :) But if will decide to come, I can assure you, that you will not be disappointed. We will do a thought experiment with one famous public high-loaded website, will look at advantages and disadvantages of SQL and NoSQL databases, and will choose the best database engine for it.
NoSQL vs SQL (by Dmitriy Beseda, JS developer and coach Binary Studio Academy)Binary Studio
It is first lecture from noSQL course for students of Lviv Polytechnic National University. Check out our educational portal: http://academy.binary-studio.com/
Если раньше при старте нового проекта нам нужно было выбрать одну из доступных на тот момент SQL баз данных, то за последние 5 лет ситуация кардинально изменилась. Теперь выбор стал гораздо сложнее. SQL или NoSQL? Сloud или on-premises? Если SQL/NoSQL - то какая именно? А может использовать и то и другое?
В данном докладе мы постараемся представить общий обзор доступных сегодня решений для хранения данных и определиться с критериями выбора.
Sebastian Cohnen – Building a Startup with NoSQL - NoSQL matters Barcelona 2014NoSQLmatters
Sebastian Cohnen – Building a Startup with NoSQL
At StormForger we use several NoSQL systems to handle all kinds of different data. We have a lot of time series data based on the fact, that we do load testing and performance analysis of HTTP-based infrastructure and services. For time series data, we use InfluxDB. We also use several Redis instances for caching and storing structured data, that needs to be fast on read and write access. Lately we also started to integrate ArangoDB into our architecture, which is a perfect fit for storing and working with our complex test case definition data structures. In this talk I’d like to present how we build our startup on the foundation provided by several NoSQL databases, how we came to choose those systems and how we use them.
SQL vs. NoSQL. It's always a hard choice.Denis Reznik
This will be an interesting and sometimes fun session with a small demo. This session will answer some of your questions and force you to think about new questions. It will not be very technical, so it's ok for choose another more technical session from the schedule :) But if will decide to come, I can assure you, that you will not be disappointed. We will do a thought experiment with one famous public high-loaded website, will look at advantages and disadvantages of SQL and NoSQL databases, and will choose the best database engine for it.
NoSQL vs SQL (by Dmitriy Beseda, JS developer and coach Binary Studio Academy)Binary Studio
It is first lecture from noSQL course for students of Lviv Polytechnic National University. Check out our educational portal: http://academy.binary-studio.com/
This presentation is dedicated to Design Patterns. The highlighted subtopics are Subsystem and Component Architecture Patterns, Concurrency Patterns, Memory Patterns, Safety and Reliability Patterns. The slides provide repeatable solutions to common software engineering problems.
This presentation by Oleh Medvedyev, Engineering Management Expert, GlobalLogic, was delivered at a GlobalLogic Embedded TechTalk in Lviv on March 29, 2017.
Microservices architecture has many benefits. But it comes at a cost. Running microservices and monitoring what’s going on is tedious. That’s why MicroProfile adopts monitoring as a first-class concept. In this session, learn how MicroProfile runtimes collect metrics and how to seamlessly collect them with tools like Prometheus and Grafana. Learn how MicroProfile makes it easy to connect information about interrelated service calls, how to gather the information and analyze system bottlenecks, how to deploy and scale MicroProfile applications with Kubernetes and how to react to their health status to detect and automatically recover from failures.
The relational database has been the dominant database model for many years. However, a new model called NoSQL is gaining significant attention. NoSQL DBs are non-relational data stores that have been employed in various scenarios, where traditional RDBMS features matter less, and the improved performance of storing or retrieving relatively simple data sets matters most. The relational and the NoSQL database model are each good for specific applications. Depending on the problem to solve, a NoSQL or a relational model can be advantageous. In this session we present some typical use cases and how they can be solved with both NoSQL and the RDMBS databases. Will there be clear a winner or is there room for both NoSQL and RDMBS in the future?
Slick (part of the Typesafe stack) is a modern database query and access library for Scala, based on functional principles. It allows you to write queries as if you are working with regular Scala collections.
In this presentation we’ll have a deep dive into how you can use this library in real projects. How to map your tables and queries to structured objects, how to create more advanced queries with multiple joins, how to setup integration tests against an in-memory database and how you can integrate Slick with the Play Framework are all questions which will have been answered at the end of this presentation.
Originally presented on the BeScala user group.
When we talk about “knowing our data,” we don’t seem to refer to the term “data integrity” anymore as part of that conversation. After all, that phrase can be very intimidating. But at its heart, it’s very simple – guaranteeing our data has meaning. The good news is much of what we already do creates data integrity in our databases.
In this presentation, we will explore how the basic constructs in our database design enforce data integrity. We will look at this from table design down through details, like data types and constraints. Additionally, we will discuss the difference between objects that support data integrity and those that support database performance.
At the end of the presentation, you will have a better understanding of what data integrity is, how to implement and enforce it in your databases, and why it is so important for our data.
View the original webcast: https://www.idera.com/resourcecentral/webcasts/geeksync/data-integrity-demystified
Azure database services for PostgreSQL and MySQLAmit Banerjee
The slide deck that Rachel and I had used to present on an overview of the managed PostgreSQL and MySQL service on Azure at SQL Saturday Redmond, 2018. This is part of the Azure Database family.
Elasticsearch in production Boston Meetup October 2014beiske
Elasticsearch easily lets you develop amazing things, and it has gone to great lengths to make Lucene's features readily available in a distributed setting. However, when it comes to running Elasticsearch in production, you still have a fairly complicated system on your hands: a system with high demands on network stability, a huge appetite for memory, and a system that assumes all users are trustworthy. This talk will cover some of the lessons we've learned from securing and herding hundreds of Elasticsearch clusters.
10 Strategies for Developing Reliable Jakarta EE & MicroProfile Applications ...Payara
Ever thought of implementing a modern cloud architecture with Jakarta EE and MicroProfile applications but don’t know which practices to follow? This talk will highlight 10 strategies that will help you implement robust scalable cloud-ready applications!
SDL Trados Studio 2014 has launched this autumn. Here an overview of all new features that have been introduced to help you enjoy your translation experience.
This presentation is dedicated to Design Patterns. The highlighted subtopics are Subsystem and Component Architecture Patterns, Concurrency Patterns, Memory Patterns, Safety and Reliability Patterns. The slides provide repeatable solutions to common software engineering problems.
This presentation by Oleh Medvedyev, Engineering Management Expert, GlobalLogic, was delivered at a GlobalLogic Embedded TechTalk in Lviv on March 29, 2017.
Microservices architecture has many benefits. But it comes at a cost. Running microservices and monitoring what’s going on is tedious. That’s why MicroProfile adopts monitoring as a first-class concept. In this session, learn how MicroProfile runtimes collect metrics and how to seamlessly collect them with tools like Prometheus and Grafana. Learn how MicroProfile makes it easy to connect information about interrelated service calls, how to gather the information and analyze system bottlenecks, how to deploy and scale MicroProfile applications with Kubernetes and how to react to their health status to detect and automatically recover from failures.
The relational database has been the dominant database model for many years. However, a new model called NoSQL is gaining significant attention. NoSQL DBs are non-relational data stores that have been employed in various scenarios, where traditional RDBMS features matter less, and the improved performance of storing or retrieving relatively simple data sets matters most. The relational and the NoSQL database model are each good for specific applications. Depending on the problem to solve, a NoSQL or a relational model can be advantageous. In this session we present some typical use cases and how they can be solved with both NoSQL and the RDMBS databases. Will there be clear a winner or is there room for both NoSQL and RDMBS in the future?
Slick (part of the Typesafe stack) is a modern database query and access library for Scala, based on functional principles. It allows you to write queries as if you are working with regular Scala collections.
In this presentation we’ll have a deep dive into how you can use this library in real projects. How to map your tables and queries to structured objects, how to create more advanced queries with multiple joins, how to setup integration tests against an in-memory database and how you can integrate Slick with the Play Framework are all questions which will have been answered at the end of this presentation.
Originally presented on the BeScala user group.
When we talk about “knowing our data,” we don’t seem to refer to the term “data integrity” anymore as part of that conversation. After all, that phrase can be very intimidating. But at its heart, it’s very simple – guaranteeing our data has meaning. The good news is much of what we already do creates data integrity in our databases.
In this presentation, we will explore how the basic constructs in our database design enforce data integrity. We will look at this from table design down through details, like data types and constraints. Additionally, we will discuss the difference between objects that support data integrity and those that support database performance.
At the end of the presentation, you will have a better understanding of what data integrity is, how to implement and enforce it in your databases, and why it is so important for our data.
View the original webcast: https://www.idera.com/resourcecentral/webcasts/geeksync/data-integrity-demystified
Azure database services for PostgreSQL and MySQLAmit Banerjee
The slide deck that Rachel and I had used to present on an overview of the managed PostgreSQL and MySQL service on Azure at SQL Saturday Redmond, 2018. This is part of the Azure Database family.
Elasticsearch in production Boston Meetup October 2014beiske
Elasticsearch easily lets you develop amazing things, and it has gone to great lengths to make Lucene's features readily available in a distributed setting. However, when it comes to running Elasticsearch in production, you still have a fairly complicated system on your hands: a system with high demands on network stability, a huge appetite for memory, and a system that assumes all users are trustworthy. This talk will cover some of the lessons we've learned from securing and herding hundreds of Elasticsearch clusters.
10 Strategies for Developing Reliable Jakarta EE & MicroProfile Applications ...Payara
Ever thought of implementing a modern cloud architecture with Jakarta EE and MicroProfile applications but don’t know which practices to follow? This talk will highlight 10 strategies that will help you implement robust scalable cloud-ready applications!
SDL Trados Studio 2014 has launched this autumn. Here an overview of all new features that have been introduced to help you enjoy your translation experience.
An outline on why the MySQL 8 release is viewed as a gamechanger with a look at some of the new features like CTEs, Window Functions, MySQL InnoDB Cluster, Enterprise Data Masking, and more
Considerations for using NoSQL technology on your next IT project - Akmal Cha...jaxconf
Over the past few years, we have seen the emergence and growth of NoSQL technology. This has attracted interest from organizations looking to solve new business problems. There are also examples of how this technology has been used to bring practical and commercial benefits to some organizations. However, since it is still an emerging technology, careful consideration is required in finding the relevant developer skills and choosing the right product. This presentation will discuss these issues in greater detail. In particular, it will focus on some of the leading NoSQL products, such as MongoDB, Cassandra, Redis, and Neo4j and will discuss their architectures and suitability for different problems. Short demonstrations, using Java, are planned to give the audience a feel for the practical aspects of such products.
OUG Scotland 2014 - NoSQL and MySQL - The best of both worldsAndrew Morgan
Understand how you can get the benefits you're looking for from NoSQL data stores without sacrificing the power and flexibility of the world's most popular open source database - MySQL.
Introducing NoSQL and MongoDB to complement Relational Databases (AMIS SIG 14...Lucas Jellema
This presentation gives an brief overview of the history of relational databases, ACID and SQL and presents some of the key strentgths and potential weaknesses. It introduces the rise of NoSQL - why it arose, what is entails, when to use it. The presentation focuses on MongoDB as prime example of NoSQL document store and it shows how to interact with MongoDB from JavaScript (NodeJS) and Java.
QuerySurge Slide Deck for Big Data Testing WebinarRTTS
This is a slide deck from QuerySurge's Big Data Testing webinar.
Learn why Testing is pivotal to the success of your Big Data Strategy .
Learn more at www.querysurge.com
The growing variety of new data sources is pushing organizations to look for streamlined ways to manage complexities and get the most out of their data-related investments. The companies that do this correctly are realizing the power of big data for business expansion and growth.
Learn why testing your enterprise's data is pivotal for success with big data, Hadoop and NoSQL. Learn how to increase your testing speed, boost your testing coverage (up to 100%), and improve the level of quality within your data warehouse - all with one ETL testing tool.
This information is geared towards:
- Big Data & Data Warehouse Architects,
- ETL Developers
- ETL Testers, Big Data Testers
- Data Analysts
- Operations teams
- Business Intelligence (BI) Architects
- Data Management Officers & Directors
You will learn how to:
- Improve your Data Quality
- Accelerate your data testing cycles
- Reduce your costs & risks
- Provide a huge ROI (as high as 1,300%)
DocumentDB is a powerful NoSQL solution. It provides elastic scale, high performance, global distribution, a flexible data model, and is fully managed. If you are looking for a scaled OLTP solution that is too much for SQL Server to handle (i.e. millions of transactions per second) and/or will be using JSON documents, DocumentDB is the answer.
Presentation given by Akmal Chaudhri (Hortonworks) to the BCS Data Management Specialist Group on 24th October 2013.
The presentation provides a balanced view of the state of NoSQL technology and tools and options for selection on projects.
A video of the presentation is available on YouTube at https://www.youtube.com/watch?v=FYfJ8C_YcvI
Polyglot Database - Linuxcon North America 2016Dave Stokes
Many Relation Databases are adding NoSQL features to their products. So what happens when you can get direct access to the data as a key/value pair, or you can store an entire document in a column of a relational table, and more
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...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.
Data at the Speed of Business with Data Mastering and GovernanceDATAVERSITY
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.
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.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
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.
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
Data Catalogs Are the Answer – What is the Question?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
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.
In this webinar, Bob will focus on:
-Selecting the appropriate metadata to govern
-The business and technical value of a data catalog
-Building the catalog into people’s routines
-Positioning the data catalog for success
-Questions the data catalog can answer
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
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.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
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.
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.
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...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.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance Trends - A Look Backwards and ForwardsDATAVERSITY
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 and Best Practices To Implement TodayDATAVERSITY
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
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.
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
Who Should Own Data Governance – IT or Business?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
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
MLOps – Applying DevOps to Competitive AdvantageDATAVERSITY
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.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...
NoSQL Now! Webinar Series: Innovations in NoSQL Query Languages
1. NoSQL Advanced Query
Languages
Using specialization and standards to drive
NoSQL database selection
Host: Dan McCreary, Kelly-McCreary & Associates
Guest: Matthias Brantner, 28msec
3. 3Kelly-McCreary & Associates
Summary
This webinar will cover the latest trends in advanced query languages
for NoSQL databases. We’ll look at how innovations in vendor-
independent standardized query languages allow NoSQL developers to
query multiple types of data and multiple NoSQL databases using a
single query language. We’ll see how using the right NoSQL query
language promotes portability across multiple NoSQL databases, avoids
vendor lock-in, and keeps your developers productive at the same
time. We will be interviewing Matthias Brantner from 28msec and see
on how they use JSONiq as a basis for a modern ETL framework that
works on a diverse number of data sources.
4. 4Kelly-McCreary & Associates
About Us
• Working with NoSQL since 2006
• Co-founders of the NoSQL Now! conference
• Authors of Manning book on NoSQL (MEAP now, print June
2013)
• Guide for managers with a focus on business benefits
• Focus on NoSQL architectural tradeoff analysis
• Published a variety of research papers on the general topics of
query processing and optimization
• Expert on XML and JSON query languages
• Studied Information Systems at the University of Mannheim and
acquired a PhD based on his research on "Rewriting Declarative
Query Language"
• Has more than 15 years of experience in database and query
technologies
5. High Level NoSQL Patterns
Relational Analytical (OLAP) Key-Value
Column-Family DocumentGraph
key value
key value
key value
key value
5
6. Query Languages
Relational: SQL
Analytical: MDX (Cubes, Categories, Measures)
key value
key value
key value
key value
Key Value Store: None (PUT, GET, DELETE)
Column Family: HIVE, PIG
Graph: SPARQL, proprietary
Document: XQuery, JSONiq
7. Distributed Computing = Distributed Queries
Traditional: Send data between nodes for "distributed joins"
NoSQL: Send queries to each node
CPU
Disk
Query
Node
CPU
Disk
CPU
Disk
CPU
Disk
CPU
Disk
Query
Response
Data
Nodes
8. Do we need 75 APIs?
"If we have 75 NoSQL databases with 75
different APIs the NoSQL movement will
never become mainstream."
Michael Stonebreaker
http://cacm.acm.org/blogs/blog-cacm/99512-why-enterprises-are-uninterested-in-nosql/fulltext
http://hpts.ws/papers/2011/sessions_2011/Stonebraker.pdf
8
9. SQL is a Platform
App1 App2 App3
RDBMS1 RDBMS2 RDBMS3
SQL ODBC, JDBC
Third Party
Applications
9
10. NoSQL is Not Yet a Platform
App1 App2 App3
NoSQL1 NoSQL2 NoSQL3
?
Third Party
Applications
Can NoSQL have a standard
API or query language?
1
0
11. 11Kelly-McCreary & Associates
Types of Data
Read Mostly
Read/Write
Structured
Unstructured
Transactional
RDBMS BI/DW
Web Crawlers
Documents
Log Files
XML
JSON
Binary
Open Linked Data
Graph
12. 12Kelly-McCreary & Associates
Diverse Needs of Databases
• Security and RBAC
• Transaction Control
• Analysis - Aggregates
• Search and Findability – XQuery fulltext, Lucene
• Spatial Queries
• Control over Clusters and Remote Data Centers
• fast vs. reliable for both reads and writes
• Consistency vs. Availability
13. 13Kelly-McCreary & Associates
Metcalf's Law and Standards
• Standards lower IT
costs
• Standard tools
• Standard libraries
• Standard training
XML
RSS
XForms
REST
14. Many Interfaces or One?
14
DB4
DB1
DB2
DB3DB5
DB6
Db7
App
DB1
DB2
DB3
DB4
DB5
DB6
DB7
Std
App
Send Data to Nodes or Queries to Nodes?
15. 15Kelly-McCreary & Associates
Standards Drive Lower Costs
• Consistent data formats
• Standardize with public data
• Example: postal code address standards
• Open linked data
• Data consistency
• Social network verifiability
• Standardized tools
• Standardize rules
• XML Schema
16. 16Kelly-McCreary & Associates
Service Insulation
• Services separate applications from databases
Corporate Data Services
App1 App2 App3
NoSQL1 NoSQL2 NoSQL3
17. 17Kelly-McCreary & Associates
Adaptors Are Inevitable!
• One library runs on may browsers – don't use proprietary APIs!
HTML
Page 1
HTML
Page 2
HTML
Page 3
18. 18Kelly-McCreary & Associates
De facto Standards
• Some interfaces achieve a dominant position by public
acceptance or market forces (such as early entrance to the
market).
• Example: Amazon S3
http://en.wikipedia.org/wiki/De_facto_standard
19. 19Kelly-McCreary & Associates
Standard for Key-Value Stores
• Note: APIs are simple but security models are non-trivial
App1 App2
S3 API (PUT, GET, DELETE)
S3 Security Models
App3
20. 20Kelly-McCreary & Associates
Challenges with Adaptors
• Added complexity
• Debugging
• Match of semantics
• Performance concerns
• Added level of indirection
• Native interfaces are always faster
• Training
• What standard can you use?
• Security
• Variety of security models for data access
22. 22Kelly-McCreary & Associates
One Database, Many Interfaces
ODBC, JDBC
SPARQL
Document
Store
Triple
Store
TablesKey Value
Store
Future DB
get, put
XQuery
JSONiq
27. 27Kelly-McCreary & Associates
Summary
1. NoSQL solutions use many diverse data formats from simple key-
value pairs to complex documents
2. NoSQL today has limited third party developers and limited use by
large companies due to concerns about application portability
3. New "common query languages" like JSONiq can handle multiple
sources in a single robust query language
4. Find out more at the NoSQL Now! conference
28. 28Kelly-McCreary & Associates
See Matthias In Person!
Do More with MongoDB and JSONiq
Matthias Brantner CTO 28msec, Inc.
http://nosql2013.dataversity.net/sessionPop.cfm?confid=7
4&proposalid=5522
• Link: http://nosqlnow.com/
29. 29Kelly-McCreary & Associates
References
• JSONiq Language Specification: http://jsoniq.org
• Demo queries used during the webinar: http://28.io/demo
• Free JSONiq book: http://www.28.io/jsoniq-the-sql-of-nosql/
• 28msec Twitter: http://twitter.com/28msec
• 28msec Blog: http://28.io/blog
• Full Text Search Specs: http://www.w3.org/TR/xpath-full-
text-10/