Cloud complexity is an inevitability. Regardless of where an organization may be on their cloud journey – on-prem, in the public cloud, or managing an expanding hybrid cloud – the reality is managing the enterprise isn’t getting any easier. Demand continues to rise for greater access to more data across the organization to do things like run analytics and machine learning and to automate more processes.
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.
Apache HBase has long been the database of choice for business-critical applications across industries. This is primarily because HBase provides unmatched scale, performance, and fault-tolerance that few other databases can come close to. Think petabytes of data spread across trillions of rows, ready for consumption in real-time.
Data is the fuel that drives government, enables transparency, and powers citizen services. But while state and local governments seek to improve policies, decision making, and the services constituents rely upon, data silos create accessibility and sharing challenges that hinder public sector agencies from transforming their data into a strategic asset and leveraging it for the common good.
