5 Steps for Implementing a Modern Data Architecture

Current market dynamics don’t allow for slowdowns. Digital disrupters have made use of innovations in AI, serverless data platforms, and seamless analytics that have completely upended traditional business models. The current market challenges presented by the Covid-19 pandemic have only exacerbated the need for fast, flexible service offerings. To remain competitive and relevant, businesses today have to move quickly to deploy new data technologies alongside legacy infrastructure to drive market-driven innovations such as personalized offers, real-time alerts, and predictive maintenance.

However, as businesses strive to implement the latest in data technology—from stream processing to analytics and data lakes—many find that their data architecture is becoming bogged down with large amounts of data that their legacy programs can’t efficiently govern or properly utilize.