Building The Backend: Data Solutions That Power Leading Organizations podcast

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Tech Podcasting Education Travis Lawrence

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محتوای ارائه شده توسط Travis Lawrence. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Travis Lawrence یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

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<div class="span index">1</div> <span><a class="" data-remote="true" data-type="html" href="/series/the-action-catalyst-2929203">The Action Catalyst</a></span>

<div class="span index">1</div> <span><a class="" data-remote="true" data-type="html" href="/series/the-action-catalyst-2929203">The Action Catalyst</a></span> podcast artwork

<div class="span index">1</div> <span><a class="" data-remote="true" data-type="html" href="/series/the-action-catalyst-2929203">The Action Catalyst</a></span> podcast artwork

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The Action Catalyst

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۲ روز پیش۲d ago

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The Action Catalyst interviews top leaders and achievers, sharing hard-earned tips and advice to help you uncover your inspiration and gain valuable insights to overcome setbacks, defeat mediocrity, and reach your goals in life, business, and beyond. Southwestern/Great American, Inc., dba Southwestern Family of Companies, for itself and its related entities and their assigns, reserves and retains all rights to their copyrighted materials and trademarks contained in this podcast.

Building the Backend: Data Solutions that Power Leading Organizations

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خانه سری•Feed

محتوای ارائه شده توسط Travis Lawrence. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Travis Lawrence یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Welcome to the Building the Backend Podcast! We’re a data podcast focused on uncovering the data technologies, processes, and patterns that are driving today’s most successful companies. You will hear from data leaders sharing their knowledge and insights with what’s working and what’s not working for them. Our goal is to bring you valuable insights that will save you and your team time when building a modern data architecture in the cloud. Topics will span from big data, AI, ML, governance, visualizations, and best practices for enabling your organization to be data-driven. If you are a chief data officer, data architect, data engineer, data analyst, and those building the backend data solutions then HIT SUBSCRIBE!

… continue reading

43 قسمت

#Tech #Podcasting Education #Travis Lawrence

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Building the Backend: Data Solutions that Power Leading Organizations

24 subscribers

updated ۳ سال پیش

اشتراک گذاری

خانه سری•Feed

محتوای ارائه شده توسط Travis Lawrence. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Travis Lawrence یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Welcome to the Building the Backend Podcast! We’re a data podcast focused on uncovering the data technologies, processes, and patterns that are driving today’s most successful companies. You will hear from data leaders sharing their knowledge and insights with what’s working and what’s not working for them. Our goal is to bring you valuable insights that will save you and your team time when building a modern data architecture in the cloud. Topics will span from big data, AI, ML, governance, visualizations, and best practices for enabling your organization to be data-driven. If you are a chief data officer, data architect, data engineer, data analyst, and those building the backend data solutions then HIT SUBSCRIBE!

… continue reading

43 قسمت

#Tech #Podcasting Education #Travis Lawrence

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The Analytics Engine for All Your Data with Justin Borgman @ Starburst 36:12

۳ years پیش36:12

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36:12

In this episode we speak with Justin Borgman, Chairman & CEO at Starburst, which is based on open source Trino (formerly PrestoSQL) and was recently valued at $3.35 billion after securing their series D funding. In this episode we discuss convergence of DW’s / DL's, why data lakes fail and much much more. Top 3 takeaways The data mesh architecture is gaining adoption more quickly in Europe due to GDPR. There were two main limitations of data lakes when comparing to DW’s, performance and CRUD operations. Performance has been resolved with query engines like Starburst and tools like Apache Iceberg, Apache Hudi and Delta Lake are starting to close the gap with CRUD operations. The principle of a single source of truth / storing everything in a single DL or DW is not always feasible or possible depending on regulations. Starburst is bridging that gap and enabling data mesh and data fabric architectures.…

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Transform Your Object Storage Into a Git-like Repository With Paul Singman @ LakeFS 27:23

۳ years پیش27:23

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In this episode we speak with Paul Singman Developer Advocate at Treeverse / LakeFS. LakeFS is an open source project that allows you to transform your object storage into a Git-like repository. Top 3 takeaways LakeFS enables use cases like debugging to quickly view historical versions of your data at a specific point in time and running ML experiments over the same set of data with branching.. The current data landscape is very fragmented with many tools available.. Over the coming years there will most likely be consolidation of tools that are more open and integrated. Data quality and observability continue to be key components of successful data lakes and having visibility into job runs.…

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Enable Faster Data Processing and Access with Apache Arrow with Matt Topol @ Factset 49:15

۳ years پیش49:15

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In this episode we speak with Matt Topol, Vice President, Principal Software Architect @ FactSet and dive deep into how they are taking advantage of Apache Arrow for faster processing and data access. Below are the top 3 value bombs: Apache Arrow is an open-source in-memory columnar format that creates a standard way to share and process data structures. Apache Arrow Flight eliminates serialization and deserialization which enables faster access to query results compared to traditional JDBC and ODBC interfaces. Don’t put all your eggs in one basket, whether you're using commercial products or open source, make sure you design a modular architecture that does not tie you down to any one piece of technology.…

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Implementing Amundsen @ Convoy with Chad Sanderson 35:52

۳ years پیش35:52

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In this episode we speak with Chad Sanderson head of data and early stage startup advisor focused on data innovation @ Convoy and uncover their journey to implementing Amundsen, an open source data catalog. Below are the top 3 value bombs: Data Scientist’s should not be spending the majority of their time trying to find the data they are interested in. Amundsen is a powerful open source data catalog that integrates across your data landscape to provide visibility into your data assets and lineage. We often get lost in the features within data teams. It’s important to take a step back and understand how you're impacting the bottom line of the business.…

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The Importance of Treating Your Data Initiatives as Products with Murali Bhogavalli 26:33

۳ years پیش26:33

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Your data team should not just be keeping the lights on, but should be building and creating data products to support the business. In this episode we speak with Murali Bhogavalli a data product manager and explore what is a data product manager and how they differ from a traditional product manager. Below are the top 3 value bombs: Data should be looked at as a product and treated as such within the organization (i.e. agile methodologies, continuous improvement…) Organizations need to be more than just data driven but also data informed. For that to happen, you need to build data literacy into your ecosystem by helping everybody understand what the data means and where is it coming from and the quality of it.. Product managers typically use data to deliver the outcomes. But for a data PM, data is the deliverable and it also the outcome.…

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Open-Source Data Catalog Amundsen with Mark Grover @ Stemma 41:11

۳ years پیش41:11

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In this episode of Building The Backend we hear from Mark Grover founder @ Stemma, co-creator of Amundsen. Stemma is a fully managed data catalog, powered by the leading open-source data catalog, Amundsen. Below are top 3 value bombs: Automated data catalogs are critical to help wrangle the growing data across organizations. (i.e. Being able to identify out of 150 columns on this table only 10 are being used downstream) Tribal knowledge and context cannot be automated - data catalogs cannot be 100% automated. Amundsen is an open-source data catalog originally created at Lyft. Stemma has created a managed version of Amundsen. Help me improve the podcast by completing this 60 second survey: https://buildingthebackend.com/survey…

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Architecting a Modern Data Lake with Dipti Borkar from Ahana 39:32

۳ years پیش39:32

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39:32

In this episode of Building The Backend we hear from Dipti Borkar cofounder @ Ahana a managed service for Presto on AWS, where we talk all about the data lake, how it should be structured and where the industry is going. Below are top 3 value bombs: Presto is an open source distributed SQL query engine originally created by Facebook, mainly used to run SQL queries on data lakes but can be connected to relational data stores as well. Ahana is a managed Presto service on AWS with 3x price/performance. When optimizing your data lake, it’s normally best to store the data in Parquet or ORC format vs JSON or CSV as they are columnar formats that can have indexes built in. Data Lake Houses are continuing to gain popularity by bringing the benefits of your data lake and data warehouse together with the help of tools like Databricks DeltaLake and Apache HUDI.…

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Open Source BI with Apache Superset 29:15

۳ years پیش29:15

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What tools are you using for data viz? Are they low cost? One option is Apache Superset, in this episode we speak with Robert Stolz to learn more about Superset and other open source data tools. Top 3 Value Bombs: One popular use case with Apache Superset is embedding it within applications because it’s open source, there is a wide range of flexibility to integrate it with existing systems. Apache Superset supports any sources supported by the Python SQL toolkit called SQLAlchemy. DBT encourages a set of best practices around data development (i.e. source control and test driven development).…

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Edge Computing and Continuous Intelligence with Swim 34:17

۳ years پیش34:17

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34:17

In this episode of Building The Backend we hear from Simon Crosby – CTO @ Swim an open source edge computing operating system, where we talk all about edge computing, event streaming and much more. Below are top 3 value bombs: Edge means more than just being physically located somewhere it could also mean in the cloud. It really is the closest point of where your source data is being generated. Continuous intelligence is a design pattern where streaming data is directly tied into business operations. Kafka is continuing to hold it’s strong position in the event streaming space.…

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12 Modern Data Architecture Principles That Should Be Implemented in 2022 20:24

۳ years پیش20:24

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20:24

This episode is a little different then the usual format. Instead of interviewing a data leader - I share what I consider are the 12 most important principles when designing a modern data architecture . Please message me on LinkedIn with the thoughts on this show.

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The Keys to Good Data Quality With Prukalpa Sankar from Atlan 37:21

۳ years پیش37:21

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In this episode of Building The Backend we hear from Prukalpa Sankar – Co-founder of Atlan, where we talk all about data quality/governance, common issues organizations face when implementing data quality and much much more. Below are top 3 value bombs: Data Governance has a bad reputation. It should not be a bureaucratic controlling process that is pushed from the top down. Active Metadata is key to modern data architectures, essentially it’s putting together all the human and machine generated metadata together to derive insights. One of the most difficult metadata attributes to capture is the context for the data as this almost always requires input from humans and tribal knowledge is often lost and is not documented.…

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Designing a Modern Data Architecture – Teradata 44:29

۴ years پیش44:29

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This is a podcast episode you do not want to miss with Stephen Brobst, CTO @ Teradata. We discuss all things Data Warehouses, the shift to the distributed cloud and, key principles to implementing successful DW's. Top 3 Value Bombs: Large organizations are shifting more to a distributed / inter-cloud architecture for many reasons, a couple of reasons are data sovereignty, increasing residency and reducing costs. Just because your DW does not support indexing does not mean you do not need them. One of the most common reasons DW’s fail is they are led by IT and not the business. The DW should be led directly by the business needs and most important initiatives.…

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Exploring Open-Source Data Integration With Airbyte 35:42

۴ years پیش35:42

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“The hardest part of ETL is not building the connectors, it is maintaining them.” Truer words never spoken. Really enjoyed this episode with Michel Tricot CEO & Co-Founder of Airbyte where we discuss all things data integration and connectors. Top 3 value bombs: The future of ETL/ELT integration connectors may lie with open source. Many closed source data integration tools only create connectors if the ROI is there, but this leaves many tools out and speed to market can be slow. Airbyte has created a modular open source framework that allows the community to quickly build reliable data connectors. As Airbyte starts to monetize they have some innovative methods, one of which is if a developer from the open source community creates and maintains a connector they could potentially get a small percentage of revenue associated with that connector. Data governance ang logging is increasingly becoming more important in the coming years.…

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How To Effectively Reduce Data Quality Incidents 10x with Datafold 39:12

۴ years پیش39:12

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39:12

This episode features Gleb Mezhanskiy Co-Founder & CEO @ Datafold, during our discussion we talk all about data observability and how to improve your data quality. Before Datafold, Gleb was a founding member of data teams at Lyft and Autodesk, where he built sophisticated data platforms and developed tooling to improve productivity and data quality. Top 3 Value Bombs: The foundation of any data observability platform is the data catalog. Data observability becomes increasingly difficult the more data sets you have if you do not define your process to track and monitor your data. Do not surprise your report consumers. knowing how your metrics will change in prod before your deployment can be done with the right data observability process and regression testing.…

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Applying Transformations to Streaming Data with Materialize 32:55

۴ years پیش32:55

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32:55

This episode features Arjun Narayan Co-Founder & CEO @ Materialize, during our discussion we talk all about transforming streaming data, the do’s the don’ts and how Materialize is changing the landscape of streaming. Top 3 Value Bombs: When creating schema changes organizations should always strive to create forward compatible schema changes only. This means consumers will be able to consume your data model without impacting them, they just may be missing your newly added column. Materialized computations are bound to change in the future, either due to bugs or requirement changes. Kafka allows you to replay all your previous messages to update the calculation. The cloud is still young, over the coming years we will see many more technologies that are specifically built with a cloud focus.…

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