The article proposes solutions to these challenges, such as the use of intelligent data lakes and object stores, AI to simplify the data landscape, and data fabric architecture to collect the right kinds of data. It emphasizes the need for user-friendly solutions that hide complexities from the end user, making them as accessible as possible to a broader audience within the enterprise. The author concludes that strategic, technically sound, and user-friendly solutions are needed to enable enterprises to confidently tackle the data landscape.
Key takeaways:
- The complexity of organizing and gathering data increases exponentially as a company's size increases, creating a multiplying problem when new applications are introduced.
- Object stores have emerged as a cost-effective and efficient solution for large volumes of data, providing a means to store vast amounts of data while ensuring quick and efficient retrieval.
- Artificial intelligence (AI) and machine learning systems can automatically identify unique signatures in data streams, reducing millions of data points to a manageable number of unique patterns.
- Data fabric architecture eliminates silos in data flow by working with different kinds of enterprises, different sizes of organizations and different technologies that may exist to streamline processes and simplify the overall data landscape.