The shift towards cloud storage has become increasingly prevalent, with a projected 60% of corporate data being stored in the cloud by 2023. In the era before cloud storage, data was contained within on-premise data centers, offering a sense of control and security. However, the modern landscape allows data to exist in three realms: on-premise, in the cloud, or within Software as a Service (SaaS) platforms, often cloud-based. Hybrid approaches, combining on-premise and cloud solutions, are common even in fully cloud-based companies.
Security and compliance are paramount concerns in this transition, with enterprises focusing on standards like ISO 27001 and SOC-2. Cloud storage offers scalability and flexibility, but it comes with associated costs. Many companies, however, lack awareness of the extent of their data, its location, and the expenses incurred for storage.
Data dispersion across multiple external SaaS applications complicates matters. For instance, 90% of Fortune 500 companies use Salesforce, but they leverage an average of 80 external SaaS apps, resulting in diverse data locations. Extracting data for analytics further multiplies versions of the same data. The author emphasizes the need for companies to understand their data landscape, considering the implications of user-based versus consumption-based pricing models.
The analogy of data hoarding is introduced, suggesting that the misconception of cheap and limitless storage has led to an accumulation of data without clear understanding or strategy. Compliance with data privacy laws, such as GDPR, requires meticulous tracking of individual data across various platforms and systems.
Looking towards the future, businesses must adopt a new mindset regarding Enterprise Data Strategy with the importance of managing the data lifecycle. A shift towards a proactive approach to data management, focusing on efficiency, innovation, and a comprehensive understanding of the entire data estate is a must. Companies must address these issues promptly to avoid potential costs in consumer trust and financial terms as data acquisition continues to accelerate.