Transforming Without Compromise: The Power of Multidimensional Scalability
Scale Without Compromise
A successful digital strategy entails more than gathering large data volumes. It requires treating data as the most important business asset that's used to solve problems, innovate faster, inform decisions, and predict the future.
Using data to predict a customer's latest preferences, when a machine part needs maintenance, or a new cost-cutting opportunity is more than a competitive advantage in today’s business environment. Optimizing data is now a necessity. Uncertainty in business can be expensive. It can be expensive in data analytics platforms, too. Organizations need to accurately predict the impact that adding hardware or users will have on a platform’s performance and cost. Many vendors define a scalable platform as a system that runs multiple queries and is able to meet future data growth needs. However, scalability must also consider important factors such as latency, performance, reliability, availability, and total cost of ownership.
That’s why a more accurate definition of scalability considers eight domains that are essential for any data analytics platform. Find out how eight dimensions of scalability allow organizations to get actionable insights from massive data workloads. Companies can ask sophisticated and new questions of all their data to drive business outcomes and achieve their goals.
A successful digital strategy entails more than gathering large data volumes. It requires treating data as the most important business asset that's used to solve problems, innovate faster, inform decisions, and predict the future.
Using data to predict a customer's latest preferences, when a machine part needs maintenance, or a new cost-cutting opportunity is more than a competitive advantage in today’s business environment. Optimizing data is now a necessity. Uncertainty in business can be expensive. It can be expensive in data analytics platforms, too. Organizations need to accurately predict the impact that adding hardware or users will have on a platform’s performance and cost. Many vendors define a scalable platform as a system that runs multiple queries and is able to meet future data growth needs. However, scalability must also consider important factors such as latency, performance, reliability, availability, and total cost of ownership.
That’s why a more accurate definition of scalability considers eight domains that are essential for any data analytics platform. Find out how eight dimensions of scalability allow organizations to get actionable insights from massive data workloads. Companies can ask sophisticated and new questions of all their data to drive business outcomes and achieve their goals.