Data Archives - Software Engineering Daily

The first industrial deployments of machine learning and artificial intelligence solutions were bespoke by definition and often had brittle operating characteristics.  Almost no one builds custom databases, web servers, or email clients.  Yet technology groups today often consider developing homegrown ML and data solutions in order to solve their unique use cases.  Today’s modern data The post Mod...

In a version control system, a Monorepo is a version control management strategy in which all your code is contained in one potentially large but complete repository.  The monorepo is in stark contrast to an alternative approach in which software teams independently manage microservices or deliver software as libraries to be imported in other projects.  The post Git Scales for Monorepos with Derri...

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 pri...

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 The post DBT: Data Build Tool with Tristan Handy appeared fi...

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...

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 The post LinearB with Dan Lines appeared first on...

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 post Modern Data Stacks Optimi...

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.  The post Instabase with...

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. The po...

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 The post Druid: E...

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: sponsor@softwareengineeringdaily.com The post DaaS with Auren Hoffman appeared first on Software Engineering Daily .

Enterprise data warehouses store all company data in a single place to be accessed, queried, and analyzed. They’re essential for business operations because they support managing data from multiple sources, providing context, and have built-in analytics tools. While keeping a single source of truth is important, easily moving data from the warehouse to other applications The post Reverse ETL: Oper...

Prophecy is a complete Low-Code Data Engineering Platform for the Enterprise. Prophecy enables all your teams on Apache Spark with a unique low-code designer. While you visually build your Dataflows – Prophecy generates high-quality Spark code on Git. Then, you can schedule Spark workflows with Prophecy’s low-code Airflow. Not only that, Prophecy provides end-to-end visibility The post Proph...

In the previous episode, Pulsar Revisited, we discussed how the company DataStax has added to their product stack Astra Streaming, their cloud-native messaging and event streaming service that’s built on top of Apache Pulsar. We discussed Apache Pulsar and the added features DataStax offers like injecting machine learning into your data streams and viewing real-time The post Pulsar Rerevisted with...

In 2003, Google developed a robust cluster management system called Borg. This enabled them to manage clusters with tens of thousands of machines, moving them away from virtual machines and firmly into container management. Then, in 2014, they open sourced a version of Borg called Kubernetes, or K8s.  Now, in 2021, CockroachDB is a distributed The post CockroachDB: Distributed Databases and Contai...

Big data analytics is the process of collecting data, processing and cleaning it, then analyzing it with techniques like data mining, predictive analytics, and deep learning. This process requires a suite of tools to operate efficiently. Data analytics can save companies money, drive product development, and give insight into the market and customers. The company The post Imply Infra: Big Data Ana...

DevOps has shortened the development life cycle for countless applications and is embraced by companies around the world. But managing and monitoring multiple environments is still a major pain point, particularly when companies need to mix cloud and legacy systems. Knowing when services go down and quickly pinpointing the cause is essential for continuous development.  The post Better Stack: A Ne...

Data science is an interdisciplinary field that combines strong technical skills with industry knowledge to perform a large range of jobs. Data scientists solve business questions with hands-on work cleaning and analyzing data, building machine learning models and applying algorithms, and generating dynamic visuals and tools to understand the world from the data it generates. The post Data Science...

Big Data has exploded the past decade as cloud computing and more efficient hardware made scaling essentially limitless. Products like Uber revolve entirely around analyzing data to provide rides. According to an EMC/IDC study, there was approximately 5.2TB of data for every person in 2020. That estimate was made before the transition to remote work, The post Data Lineage: Understanding Data Linea...

There are over 4 billion people using email. Many people using email for business communicate quick questions to colleagues, send repetitive, template-based information to potential customers and freshly hired employees, and repeat a lot of the same phrases. We actually repeat phrases in a lot of written formats. How often do you copy and paste The post Text Blaze: Text Shortcuts with Scott Fortma...

Continuous integration is a coding practice where engineers deliver incremental and frequent code changes to create higher quality software and collaborate more. Teams attempting to continuously integrate new code need a consistent and automated pipeline for reviewing, testing, and deploying the changes. Otherwise change requests pile up in the queue and nothing gets integrated efficiently.  The p...

ELT is a process for copying data from a source system into a target system. It stands for “Extract, Load, Transform” and starts with extracting a copy of data from the source location. It’s loaded into the target system like a data warehouse, and then it’s ready to be transformed into a usable format for The post Meltano: ELT for DataOps with Douwe Maan appeared first on Software Engineering Dail...

Uber is one of many examples we’ve discussed on this show that has changed the world with big data analysis. With over 8 million users, 1 billion Uber trips and people driving for Uber in over 400 cities and 66 countries, Uber has redefined an entire industry in a very short time frame. It’s difficult The post Uber Data Science with Kevin Novak appeared first on Software Engineering Daily .

The quantity and quality of a company’s data can mean the difference between a major success or major failure. Companies like Google have used big data from its earliest days to steer their product suite in the direction consumers need. Other companies, like Apple, didn’t always use big data analytics to drive product design, but The post Axiom Browser Automation with Yaseer Sheriff appeared first...

The company StreamSets is enabling DataOps practices in today’s enterprises. StreamSets is a data engineering platform designed to help engineers design, deploy, and operate smart data pipelines. StreamSets Data Collector is a codeless solution for designing pipelines, triggering CDC operations, and monitoring data in flight. StreamSets Transformer uses Apache Spark to generate insights about your...