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.
Have you ever woken up to a crisis because a number on a dashboard is broken and no one knows why? Or sent out frustrating slack messages trying to find the right data set? Or tried to understand what a column name means?
Our friends at Atlan started out as a data team themselves and faced all this collaboration chaos themselves, and started building Atlan as an internal tool for themselves. Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. By acting as a virtual hub for data assets ranging from tables and dashboards to SQL snippets & code, Atlan enables teams to create a single source of truth for all their data assets, and collaborate across the modern data stack through deep integrations with tools like Snowflake, Slack, Looker and more.
Go to dataengineeringpodcast.com/atlan and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription.
Your data platform needs to be scalable, fault tolerant, and performant, which means that you need the same from your cloud provider. Linode has been powering production systems for over 17 years, and now they’ve launched a fully managed Kubernetes platform. With the combined power of the Kubernetes engine for flexible and scalable deployments, and features like dedicated CPU instances, GPU instances, and object storage you’ve got everything you need to build a bulletproof data pipeline. If you go to dataengineeringpodcast.com/linode today you’ll even get a $100 credit to use on building your own cluster, or object storage, or reliable backups, or… And while you’re there don’t forget to thank them for being a long-time supporter of the Data Engineering Podcast!
Satori created the first DataSecOps solution which streamlines data access while solving the most difficult security and privacy challenges. The Secure Data Access Service is a universal visibility and control plane across all data stores, allowing you to oversee your data and its usage in real-time while automating access controls. The service maps all of the organization’s sensitive data and monitors all data flows in real-time across all data stores. Satori enables your organization to replace cumbersome permissions with streamlined just-in-time data access workflows. It acts as a universal policy engine for data access by enforcing access policies, masking or anonymizing data, and initiating off-band access workflows.
Satori integrates into your environment in minutes by simply replacing the data store URL. Since Satori’s solution is transparent, there is no need to change your existing data flow or data store configuration. Go to dataengineeringpodcast.com/satori today and get a $5K credit for your next Satori subscription.
- Hello and welcome to the Data Engineering Podcast, the show about modern data management
- When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show!
- Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. By acting as a virtual hub for data assets ranging from tables and dashboards to SQL snippets & code, Atlan enables teams to create a single source of truth for all their data assets, and collaborate across the modern data stack through deep integrations with tools like Snowflake, Slack, Looker and more. Go to dataengineeringpodcast.com/atlan today and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription
- Have you ever had to develop ad-hoc solutions for security, privacy, and compliance requirements? Are you spending too much of your engineering resources on creating database views, configuring database permissions, and manually granting and revoking access to sensitive data? Satori has built the first DataSecOps Platform that streamlines data access and security. Satori’s DataSecOps automates data access controls, permissions, and masking for all major data platforms such as Snowflake, Redshift and SQL Server and even delegates data access management to business users, helping you move your organization from default data access to need-to-know access. Go to dataengineeringpodcast.com/satori today and get a $5K credit for your next Satori subscription.
- Your host is Tobias Macey and today I’m interviewing Saket Saurabh, Maarten Masschelein, Akshay Deshpande, and Dan Weitzner about the challenges facing data practitioners today and the solutions that are being brought to market for addressing them, as well as the work they are doing that got them recognized as "cool vendors" by Gartner.
- How did you get involved in the area of data management?
- Can you each describe what you view as the biggest challenge facing data professionals?
- Who are you building your solutions for and what are the most common data management problems are you all solving?
- What are different components of Data Management and why is it so complex?
- What will simplify this process, if any?
- The report covers a lot of new data management terminology – data governance, data observability, data fabric, data mesh, DataOps, MLOps, AIOps – what does this all mean and why is it important for data engineers?
- How has the data management space changed in recent times? Describe the current data management landscape and any key developments.
- From your perspective, what are the biggest challenges in the data management space today? What modern data management features are lacking in existing databases?
- Gartner imagines a future where data and analytics leaders need to be prepared to rely on data management solutions that make heterogeneous, distributed data appear consolidated, easy to access and business friendly. How does this tally with your vision of the future of data management and what needs to happen to make this a reality?
- What are the most interesting, innovative, or unexpected ways that you have seen your respective products used (in isolation or combined)?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on your respective platforms?
- What are the upcoming trends and challenges that you are keeping a close eye on?
- From your perspective, what is the biggest gap in the tooling or technology for data management today?