One:
Choosing The Right Technology
Choosing The Right Technology
Enterprises face challenges of overcoming the limitations of existing legacy technology and providing the performance necessary to drill into data at scale. The full analytics stack relies on three components:
- A data warehouse that can support the capacity demands of the business
- A modeling platform to provide consistent data definitions analysts can use to drill into data
- A visualization tool to derive the insights that are ultimately used to make business decisions.
The first step in choosing the right technology is to establish the goals of your organization and answering the question: What are the business outcomes that you’re trying to achieve? You may be focused on being data-driven at scale to leverage rapidly growing data volumes, reducing reliance on IT in order to accelerate reporting and time-to-insight, or enabling granular drill-down analysis capabilities to better identify business opportunities – or a combination of these.
With your goals established, it’s important to define your technology evaluation criteria. Criteria should drive performance and ultimately our business goals. Examples of these are the capacity of the platform, usage of the platform, and the compute cost of the dashboard or data model.
You should be able to measure the results of your technology choices as well, using KPIs such as the number of data requests being managed across teams, query performance, and number of data sources being accessed regularly.