Summary Aerospike is a database engine that is designed to provide millisecond response times for queries across terabytes or petabytes. In this episode Chief Strategy Officer, Lenley Hensarling, explains how the ability to process these large volumes of information in real-time allows businesses to unlock entirely new capabilities. He also discusses the technical implementation that allows for such extreme performance and how the data model contributes to the scalability of the system. If you n...
Oct 02, 2021•1 hr 8 min•Ep. 226
Summary The promise of online services is that they will make your life easier in exchange for collecting data about you. The reality is that they use more information than you realize for purposes that are not what you intended. There have been many attempts to harness all of the data that you generate for gaining useful insights about yourself, but they are generally difficult to set up and manage or require software development experience. The team at Prifina have built a platform that allows...
Sep 30, 2021•1 hr 12 min•Ep. 225
Summary The accuracy and availability of data has become critically important to the day-to-day operation of businesses. Similar to the practice of site reliability engineering as a means of ensuring consistent uptime of web services, there has been a new trend of building data reliability engineering practices in companies that rely heavily on their data. In this episode Egor Gryaznov explains how this practice manifests from a technical and organizational perspective and how you can start adop...
Sep 26, 2021•58 min•Ep. 224
Summary Python has beome the de facto language for working with data. That has brought with it a number of challenges having to do with the speed and scalability of working with large volumes of information.There have been many projects and strategies for overcoming these challenges, each with their own set of tradeoffs. In this episode Ehsan Totoni explains how he built the Bodo project to bring the speed and processing power of HPC techniques to the Python data ecosystem without requiring any ...
Sep 25, 2021•1 hr 4 min•Ep. 223
Summary Building, scaling, and maintaining the operational components of a machine learning workflow are all hard problems. Add the work of creating the model itself, and it’s not surprising that a majority of companies that could greatly benefit from machine learning have yet to either put it into production or see the value. Tristan Zajonc recognized the complexity that acts as a barrier to adoption and created the Continual platform in response. In this episode he shares his perspective...
Sep 19, 2021•1 hr 12 min•Ep. 222
Summary Biology has been gaining a lot of attention in recent years, even before the pandemic. As an outgrowth of that popularity, a new field has grown up that pairs statistics and compuational analysis with scientific research, namely bioinformatics. This brings with it a unique set of challenges for data collection, data management, and analytical capabilities. In this episode Jillian Rowe shares her experience of working in the field and supporting teams of scientists and analysts with the d...
Sep 19, 2021•55 min•Ep. 221
Summary The Cassandra database is one of the first open source options for globally scalable storage systems. Since its introduction in 2008 it has been powering systems at every scale. The community recently released a new major version that marks a milestone in its maturity and stability as a project and database. In this episode Ben Bromhead, CTO of Instaclustr, shares the challenges that the community has worked through, the work that went into the release, and how the stability and testing ...
Sep 12, 2021•59 min•Ep. 220
Summary Gartner analysts are tasked with identifying promising companies each year that are making an impact in their respective categories. For businesses that are working in the data management and analytics space they recognized the efforts of Timbr.ai, Soda Data, Nexla, and Tada. In this episode the founders and leaders of each of these organizations share their perspective on the current state of the market, and the challenges facing businesses and data professionals today. Announcements He...
Sep 09, 2021•1 hr 4 min•Ep. 219
Summary The term "data platform" gets thrown around a lot, but have you stopped to think about what it actually means for you and your organization? In this episode Lior Gavish, Lior Solomon, and Atul Gupte share their view of what it means to have a data platform, discuss their experiences building them at various companies, and provide advice on how to treat them like a software product. This is a valuable conversation about how to approach the work of selecting the tools that you us...
Sep 04, 2021•1 hr•Ep. 218
Summary The Presto project has become the de facto option for building scalable open source analytics in SQL for the data lake. In recent months the community has focused their efforts on making it the fastest possible option for running your analytics in the cloud. In this episode Dipti Borkar discusses the work that she and her team are doing at Ahana to simplify the work of running your own PrestoDB environment in the cloud. She explains how they are optimizin the runtime to reduce latency an...
Sep 02, 2021•1 hr 1 min•Ep. 217
Summary The reason that so much time and energy is spent on data integration is because of how our applications are designed. By making the software be the owner of the data that it generates, we have to go through the trouble of extracting the information to then be used elsewhere. The team at Cinchy are working to bring about a new paradigm of software architecture that puts the data as the central element. In this episode Dan DeMers, Cinchy’s CEO, explains how their concept of a "D...
Aug 28, 2021•51 min•Ep. 216
Summary The technological and social ecosystem of data engineering and data management has been reaching a stage of maturity recently. As part of this stage in our collective journey the focus has been shifting toward operation and automation of the infrastructure and workflows that power our analytical workloads. It is an encouraging sign for the industry, but it is still a complex and challenging undertaking. In order to make this world of DataOps more accessible and manageable the team at Nex...
Aug 25, 2021•58 min•Ep. 215
Summary Data lakes have been gaining popularity alongside an increase in their sophistication and usability. Despite improvements in performance and data architecture they still require significant knowledge and experience to deploy and manage. In this episode Vikrant Dubey discusses his work on the Cuelake project which allows data analysts to build a lakehouse with SQL queries. By building on top of Zeppelin, Spark, and Iceberg he and his team at Cuebook have built an autoscaled cloud native s...
Aug 21, 2021•28 min•Ep. 214
Summary A major concern that comes up when selecting a vendor or technology for storing and managing your data is vendor lock-in. What happens if the vendor fails? What if the technology can’t do what I need it to? Compilerworks set out to reduce the pain and complexity of migrating between platforms, and in the process added an advanced lineage tracking capability. In this episode Shevek, CTO of Compilerworks, takes us on an interesting journey through the many technical and social comple...
Aug 18, 2021•1 hr 6 min•Ep. 213
Summary The vast majority of data tools and platforms that you hear about are designed for working with structured, text-based data. What do you do when you need to manage unstructured information, or build a computer vision model? Activeloop was created for exactly that purpose. In this episode Davit Buniatyan, founder and CEO of Activeloop, explains why he is spending his time and energy on building a platform to simplify the work of getting your unstructured data ready for machine learning. H...
Aug 15, 2021•49 min•Ep. 212
Summary All of the fancy data platform tools and shiny dashboards that you use are pointless if the consumers of your analysis don’t have trust in the answers. Stemma helps you establish and maintain that trust by giving visibility into who is using what data, annotating the reports with useful context, and understanding who is responsible for keeping it up to date. In this episode Mark Grover explains what he is building at Stemma, how it expands on the success of the Amundsen project, an...
Aug 10, 2021•53 min•Ep. 211
Summary Every organization needs to be able to use data to answer questions about their business. The trouble is that the data is usually spread across a wide and shifting array of systems, from databases to dashboards. The other challenge is that even if you do find the information you are seeking, there might not be enough context available to determine how to use it or what it means. Castor is building a data discovery platform aimed at solving this problem, allowing you to search for and doc...
Aug 07, 2021•53 min•Ep. 210
Summary Data lake architectures have largely been biased toward batch processing workflows due to the volume of data that they are designed for. With more real-time requirements and the increasing use of streaming data there has been a struggle to merge fast, incremental updates with large, historical analysis. Vinoth Chandar helped to create the Hudi project while at Uber to address this challenge. By adding support for small, incremental inserts into large table structures, and building suppor...
Aug 03, 2021•1 hr 10 min•Ep. 209
Summary Companies of all sizes and industries are trying to use the data that they and their customers generate to survive and thrive in the modern economy. As a result, they are relying on a constantly growing number of data sources being accessed by an increasingly varied set of users. In order to help data consumers find and understand the data is available, and help the data producers understand how to prioritize their work, SelectStar has built a data discovery platform that brings everyone...
Jul 31, 2021•51 min•Ep. 208
Summary Everyone expects data to be transmitted, processed, and updated instantly as more and more products integrate streaming data. The technology to make that possible has been around for a number of years, but the barriers to adoption have still been high due to the level of technical understanding and operational capacity that have been required to run at scale. Datastax has recently introduced a new managed offering for Pulsar workloads in the form of Astra Streaming that lowers those barr...
Jul 28, 2021•1 hr•Ep. 207
Summary Collecting and cleaning data is only useful if someone can make sense of it afterward. The latest evolution in the data ecosystem is the introduction of a dedicated metrics layer to help address the challenge of adding context and semantics to raw information. In this episode Nick Handel shares the story behind Transform, a new platform that provides a managed metrics layer for your data platform. He explains the challenges that occur when metrics are maintained across a variety of syste...
Jul 23, 2021•1 hr 1 min•Ep. 206
Summary Data quality is a concern that has been gaining attention alongside the rising importance of analytics for business success. Many solutions rely on hand-coded rules for catching known bugs, or statistical analysis of records to detect anomalies retroactively. While those are useful tools, it is far better to prevent data errors before they become an outsized issue. In this episode Gleb Mezhanskiy shares some strategies for adding quality checks at every stage of your development and depl...
Jul 20, 2021•1 hr 1 min•Ep. 205
Summary There is a wealth of tools and systems available for processing data, but the user experience of integrating them and building workflows is still lacking. This is particularly important in large and complex organizations where domain knowledge and context is paramount and there may not be access to engineers for codifying that expertise. Raj Bains founded Prophecy to address this need by creating a UI first platform for building and executing data engineering workflows that orchestrates ...
Jul 16, 2021•1 hr 13 min•Ep. 204
Summary We have been building platforms and workflows to store, process, and analyze data since the earliest days of computing. Over that time there have been countless architectures, patterns, and "best practices" to make that task manageable. With the growing popularity of cloud services a new pattern has emerged and been dubbed the "Modern Data Stack". In this episode members of the GoDataDriven team, Guillermo Sanchez, Bram Ochsendorf, and Juan Perafan, explain the combin...
Jul 13, 2021•49 min•Ep. 203
Summary Every data project, whether it’s analytics, machine learning, or AI, starts with the work of data cleaning. This is a critical step and benefits from being accessible to the domain experts. Trifacta is a platform for managing your data engineering workflow to make curating, cleaning, and preparing your information more approachable for everyone in the business. In this episode CEO Adam Wilson shares the story behind the business, discusses the myriad ways that data wrangling is per...
Jul 09, 2021•1 hr 7 min•Ep. 202
Summary At the core of every data pipeline is an workflow manager (or several). Deploying, managing, and scaling that orchestration can consume a large fraction of a data team’s energy so it is important to pick something that provides the power and flexibility that you need. SaaSGlue is a managed service that lets you connect all of your systems, across clouds and physical infrastructure, and spanning all of your programming languages. In this episode Bart and Rich Wood explain how SaaSGl...
Jul 05, 2021•56 min•Ep. 201
Summary Data integration in the form of extract and load is the critical first step of every data project. There are a large number of commercial and open source projects that offer that capability but it is still far from being a solved problem. One of the most promising community efforts is that of the Singer ecosystem, but it has been plagued by inconsistent quality and design of plugins. In this episode the members of the Meltano project share the work they are doing to improve the discovery...
Jul 03, 2021•1 hr 5 min•Ep. 200
Summary While the overall concept of timeseries data is uniform, its usage and applications are far from it. One of the most demanding applications of timeseries data is for application and server monitoring due to the problem of high cardinality. In his quest to build a generalized platform for managing timeseries Paul Dix keeps getting pulled back into the monitoring arena. In this episode he shares the history of the InfluxDB project, the business that he has helped to build around it, and th...
Jun 29, 2021•1 hr 6 min•Ep. 199
Summary Data Engineering is a broad and constantly evolving topic, which makes it difficult to teach in a concise and effective manner. Despite that, Daniel Molnar and Peter Fabian started the Pipeline Academy to do exactly that. In this episode they reflect on the lessons that they learned while teaching the first cohort of their bootcamp how to be effective data engineers. By focusing on the fundamentals, and making everyone write code, they were able to build confidence and impart the importa...
Jun 26, 2021•1 hr 11 min•Ep. 198
Summary The database is the core of any system because it holds the data that drives your entire experience. We spend countless hours designing the data model, updating engine versions, and tuning performance. But how confident are you that you have configured it to be as performant as possible, given the dozens of parameters and how they interact with each other? Andy Pavlo researches autonomous database systems, and out of that research he created OtterTune to find the optimal set of parameter...
Jun 23, 2021•58 min•Ep. 197
