Companies that gather data about their users have an ethical obligation and legal responsibility to protect the personally identifiable information in their dataset.  Ideally, developers working on a software application wouldn’t need access to production data. Yet without high-quality example data, many technology groups stumble on avoidable problems.  Organizations need a solution to protect privacy while simultaneously preserving aspects of the data which are important.

Tonic is automating data synthesis to advance data privacy.  Their solution gives your production-like data for development and analytical purposes without compromising on data quality or privacy.  In this episode, I interview Tonic’s CEO Ian Coe, and Head of Engineering Adam Kamor.

Sponsorship inquiries: [email protected]

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Applications write data to persistent storage like a database.  The most popular database query language is SQL which has many similar dialects.  SQL is expressive and powerful for describing what data you want.  What you do with that data requires a solution in the form of a data pipeline.  Ideally, these analytical workflows can follow similar best practices to those handled in application code.

DBT is a transformation workflow that lets teams deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Users who know SQL can build production-grade data pipelines.  In this episode, I interview Tristan Handy, CEO, and founder of DBT Labs.

Sponsorship inquiries: [email protected]

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Tedious, repetitive tasks are better handled by machines.  Unless these tasks truly require human intelligence, repetitive tasks are often good candidates for automation.  Implementing process automation can be challenging and technical.  Increasingly, engineers are seeking out tools and platforms to facilitate faster, more reliable automation.

In this episode I talk to Yaseer Sheriff, Co-Founder and CEO at Axiom about no-code solutions, process automation, and some of the challenges in developing the software powering those services.

Sponsorship inquiries: [email protected]

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A developer’s core deliverables are individual commits and the pull requests they aggregate into. While the number of lines of code written alone may not be very informative, in total, the code and metadata about the code found in tracking systems present a rich dataset with great promise for analysis and productivity optimization insights.

LinearB is a systematic approach to engineering improvement. Their WorkerB Slack Bot connects with teams on an individual level to help with productivity and collaboration. In this episode, I speak with Dan Lines, Co-Founder, and COO.

Sponsorship inquiries: [email protected]

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Modern companies leverage dozens or even hundreds of software solutions to solve specific needs of the business.  Organizations need to collect all these disparate data sources into a data warehouse in order to add value.  The raw data typically needs transformation before it can be analyzed.  In many cases, companies develop homegrown solutions, thus reinventing the wheel and possibly planting deep rooted seeds of technical debt.

Mozart Data helps you collect all of your data sources in under an hour.  They provide managed data pipelines, data warehousing, and transformation automation.  In this episode, I interview CEO Peter Fishman and CTO Dan Silberman about the modern data stack.

Sponsorship inquiries: [email protected]

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Instabase is a technology platform for building automation solutions. Users deploy it onto their own infrastructure and can leverage the tools offered by the platform to build complex workflows for handling tasks like income verification and claims processing.

In this episode we interview Anant Bhardwaj, founder of Instabase. He describes Instabase as an operating system.  We explore what he means by that and discuss the types of use cases Instabase powers.

Sponsorship inquiries: [email protected]

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Time series data are simply measurements or events that are tracked, monitored, downsampled, and aggregated over time. This could be server metrics, application performance monitoring, network data, sensor data, events, clicks, trades in a market, and many other types of analytics data (influxdata.com).

The platform InfluxData is designed for building and operating time series applications. InfluxData is engineered for growth with enterprise-grade security, ingests metrics, events and logs in a high-performing time series database, and platform analytics for detecting and resolving problems.

In this episode we talk to Russ Savage, Director of Product Management at InfluxData.

Full disclosure: InfluxData is a sponsor of Software Engineering Daily.

Sponsorship inquiries: [email protected]

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Whether sending messages, shopping in an app, or watching videos, modern consumers expect information and responsiveness to be near-instant in their apps and devices. From a developer’s perspective, this means clean code and a fast database. 

Apache Druid is a database built to power real-time analytic workloads for event-driven data, like user-facing applications, streaming, and anything else that requires instant data visibility. Druid offers lower latency for OLAP-style queries, time-based partitioning, fast search and filter, and out-of-the-box integration with Apache Kafka, AWS Kinesis, HDFS, AWS S3, and more (Druid.apache.org).

In this episode we talk with Eric Tschetter, Field CTO at Imply, Fellow at Splunk, and experience developing large swaths of backend infrastructure largely focusing on Druid. We discuss the use cases and power of Apache Druid.

Sponsorship inquiries: [email protected]

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Auren Hoffman is the CEO of SafeGraph. In this episode we discuss data as a service and more.

This interview was also recorded as a video podcast. Check out the video on the Software Daily YouTube channel.

Sponsorship inquiries: [email protected]

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