You want to enable analytics, data science, or applications with data so you can answer questions, predict outcomes, discover relationships, or grow your business. But to do any of that, data must be stored in a manner to support these outcomes. This may be a simple decision when supporting a small, well-known use case, but it quickly becomes complicated as you scale the data volume, variety, workloads, and use cases.
Software company Slack is on a mission to make work simpler, more pleasant, and more productive. Millions of users across more than 150 countries use Slack to collaborate with team members, connect other tools and services, and access information. Marketers at Slack rely on large amounts of data to build custom audiences, manage subscriber consent preferences, and measure campaign performance.
Snowflake recently announced results from the 2022 Customer Experience Survey. Hopefully, you’ve already heard about Snowflake’s overall Net Promoter Score (NPS) of 72*, a score more than three times the industry average of 21, based on the Qualtrics 2021 NPS Industry Benchmarking Report. The survey also asked customers for feedback on specific Snowflake experiences along the customer journey, from initially researching the product to implementation to getting help and support when needed.
About 80% of the world’s data is unstructured. Unstructured data within documents, emails, web pages, images, comments on blogs and social media sites, and more can be extraordinarily valuable, making the ability to process this kind of data vital for organizations that want to make data-driven decisions.
Snowflake’s Data Cloud is powered by a single engine. From day 1, we have been focusing on consistently evolving and improving this engine to allow existing workloads to run more efficiently and enable new workloads to run on Snowflake. The single engine approach translates into a single experience—from one consistent pricing model to an integrated approach combining performance, security, governance, and the foundation to seamlessly enable cross-region or cross-cloud scenarios.
Going into Snowflake Summit 2022, I was excited to spend time with our customers and partners, and excited to be able to share some of the innovations we’ve been working on. And I was not disappointed! It felt great to experience the energy that only an in-person event can deliver. I relished talking to customers about how our products can help them meet and even surpass their business goals.
Snowflake has once again transformed data management and data analytics with our newest workload—Unistore. For decades, transactional and analytical data have remained separate, significantly limiting how fast organizations could evolve their businesses. With Unistore, organizations can use a single, unified data set to develop and deploy applications, and analyze both transactional and analytical data together in near-real time.
Cybersecurity is a data problem at its core. Yet, security teams haven’t achieved tremendous success in utilizing the modern data stack that data analytics teams have enjoyed for years. Security teams face constant pressure from vulnerabilities and breaches in their infrastructure and supply chains because they remain on a proverbial island with antiquated technology. Cybersecurity leaders must uplevel their strategies by implementing a modern security data lake.
How we eat, exercise, work, and rest play an important role in influencing our health outcomes. It’s been established that healthcare and life sciences (HCLS) organizations can improve health outcomes when they have access to this type of data on patients to inform real-world evidence.
Machine learning (ML), more than any other workflow, has imposed the most stress on modern data architectures. Its success is often contingent on the collaboration of polyglot data teams stitching together SQL- and Python-based pipelines to execute the many steps that take place from data ingestion to ML model inference.
