Webinars

Webinars

  • Exploring Test Data Flow using Apache Pulsar

    Testing is an indispensable and potentially a very expensive part of the software development life cycle. Data-driven testing (DDT) is a software testing methodology that essentially separates the test data from the test script, which lends itself particularly well to conceptualize an automation framework, in which testing is triggered on sets of data sources. This automated framework resolves the lengthy and time-consuming process of creating individual test cases for each data set. Traditionally, the test data sources are stored in files or databases, but with today’s modern computing infrastructure, we want to look at event streams as the data source. One advantage of leveraging on event streams is the ability to ingest high volumes of data with low latency in the response time. This talk will introduce you to event streaming and processing, and, among a wide range of systems that it is suited for, we will focus on how it can help you build systems for doing specific QA tasks such as performance and volume/spike testing. We will work on building a simple test data pipeline using a powerful open source streaming platform called Apache Pulsar. Read More

  • Powering AI/ML Operational Innovation with Generative Synthetic Data

    Data has become the fuel that powers the Artificial Intelligence ecosystem. Global enterprises continue to face hurdles in training, development and testing of AI/ML models by Dev & Test teams, Data Scientists and MLOps teams: (a) access to data and sharing data is impeded by restrictions and regulations, (b) retention and storage of raw data is expensive and, (c) sparseness and bias in data. Gartner predicts that by 2024, 60% of data used for the development of AI and analytics projects will be synthetically generated. In this webinar, we will discuss how synthetic data can help maximize the usefulness of data by safely sharing it with whom, when and what. We will describe how recent advances in AI Generative Adversarial Networks (GANs) models can be used with structured, time series, incident log and session journey data effectively to create high-fidelity synthetic data that addresses privacy challenges. Read More

  • Modernize Your Software Development Process

    Digital acceleration brought on by the pandemic environment has put unprecedented pressure on software development teams in every industry. This new reality demands that software engineering leaders must re-evaluate their processes and take steps to modernize their teams, practices and tools, focusing on workflow automation, security integration and expedited operations. This panel of experts will explore the strategies forward-thinking software development teams should consider adopting to improve their processes and ensure they can meet modern-day demands. Join us to learn about: --Developer platforms and environments --Low-code/no-code options --Streamlining workflow with analytics --Automated testing Read More

  • Just Build It! How to Make MLOps a Reality In Your Organisation

    Orchestrating data science and machine learning in an industrial setting is difficult. The data landscape is challenging, littered with complex problems and without the necessary freedom to design experiments or create observational studies on real-world processes. On top of that, you must manage stakeholders, operate cloud technologies, write software or wrap your solution into a product required to run predictions 24/7/365 – all while supporting business operations! With all this on your plate, you will need strategies to successfully incorporate MLOps in your organisation. In this talk, we will explore: How to “bootstrap” ML Engineering (MLEng) and MLOps practices in your organisation. Different ways to organize your MLOps teams to create optimum value. Where to start on your MLOps journey. How to avoid some common “gotchas” of starting out in MLOps. Read More

  • DevSecOps and Agile Transformation – Best Practices and Lessons Learnt

    For competitive survival, continuous improvement in product development capability is very important. DevSecOps and Agile development are two very important framework for going in that direction though rolling out them may be fraught with challenges. There can be several reasons for that. This webinar will focus upon some of the best practices and lessons learnt from speaker’s past experience in multiple organizations and multiple products. This may benefit in making these transformations successful in your own organizations. Read More

  • Building a Data Architecture that Adds Value to Your Business

    Many organizations are rightly focusing on making sure that their data is being managed, governed, and quality controlled. While this is necessary, it is not enough to add value to the business. For this investment to pay off, the data has to be used to drive decisions. This is easier said than done, and requires careful planning upfront to ensure that your architecture is built in a way that will be able to do more than reporting. I will discuss what steps you need to take before you go too far in your data journey. Key Takeaways: Learn what is needed for your data investment to pay off. What are some common mistakes? What to watch for in the coming years? Read More

  • Streaming Analytics for No-Code, Low-Code or Loadsa-Code

    Whatever your preferred form of analytics, interface preferences, coding skills, or architecture – cloud, on-premises or hybrid - handling more data more simply is in easy reach. In this session, we will explore, with examples from multiple industries, 3 simple steps data scientists, analysts and their teams can take to run powerful, scalable real-time analytics that reduce compute costs, data complexity, and risks. They include: • simplifying data management and storage processes, including real-time data. • automating and integrating continuous intelligence that combines new and historical data. • customizing code and visualization to drive faster, more useful decisions, commensurate with your organization’s bespoke needs and unique culture. Read More

  • Decision intelligence unleashed: Analytics to drive smarter decision-making

    Cloud data warehouses have fundamentally changed the way businesses capture and store data, making more complete and complex analysis possible than ever before. While most aspects of the modern data stack have continued to evolve, reporting and business intelligence tools haven’t delivered new ways to explore data and uncover ‘why’ a key metric changed. It’s time to augment manual reporting and BI workflows. Decision intelligence allows data analysts to leverage the power of machine learning and AI to quickly and comprehensively analyze cloud-scale data—uncovering statistically relevant factors impacting metric change. By using decision intelligence along with BI workflows, data analysts can fully leverage the high-volume, high-dimensional data to quickly answer ‘why’ KPIs change and guide decision-making. In this webinar you’ll learn: -Industry trends driving the next wave of data and analytics—decision intelligence—forward -Data analyst workflows for using Sisu with BI tools, specifically highlighting using LookML to create datasets for Sisu -Real-world examples of companies improving decision-making with decision intelligence Read More

  • Accelerate Time to Insight with an Open Lakehouse Architecture

    Data teams are challenged with an explosion of data, and increased demand for analytic insights from a wide range of data consumers. Cloud data lakes represent the first destination for the newest and fastest-growing sources of customer and operational data, but making that data accessible for Business Intelligence and reporting workloads typically requires building and maintaining complex, manual, and ad hoc ETL processes and proliferating data copies. In this session, learn how an open lakehouse architecture simplifies and streamlines access to the data lake, and enables self-service analytics for technical and non-technical data consumers. Read More

  • Cross-cloud analytics and visualization with BigQuery Omni and Looker

    The increasing adoption of multicloud is leading to business-critical data getting more siloed. This makes it difficult and time-consuming for data engineers, architects, and analysts to quickly gain value from data. BigQuery Omni connects to various cloud data sources and provides a single pane of glass to access the data using SQL – like queries without leaving the interface. Looker allows you to explore, share, and visualize your company’s data to make better business decisions. In this session, you’ll see a demo of how to break down data silos using BigQuery Omni and Looker to securely and cost effectively analyze and visualize data across clouds. Read More