Enterprise Software: The Vision of a Modern Data Estate Appeals but Difficult to Achieve

Cloud Computing has changed expectations about enterprise software. Traditionally, enterprise software was planned and built over the course of many months or even years. The process which included the design, architecting, implementation, and testing was a very tedious and expensive undertaking that often ended up with an application that was seriously dated by the time it was deployed.

The ready availability of cloud computing and infrastructure has significantly improved the ability and timeline needed to create targeted applications that roll out and scale quickly. Data Analytics and Business Intelligence applications are no exception. The Modern Data Estate is a term used to describe the improved applications that businesses can now roll out for cloud-based real-time data processing.

The Modern Data Estate is enabled by cloud storage and data virtualization. Data virtualization is a standard method for accessing any kind of data that a business has, data that could have originated from one of many different locations and applications, and stored in a wide array of possible different formats.

Heine Krog Iversen, CEO at TimeXtender, said that “having a ‘contemporary’ [modern] data estate is even more vital to a corporation when we understand that the growth rate of the amount of raw data coming into a company is astronomical. The good news is that we’re well along the life cycle curve, and mature technologies are now available to allow companies to build out their progressive data estate.”

Maybe. While the data estate vision is compelling and the basic components for building a Modern Data Estate are available, it hasn’t been easy or cheap. A report from Forrester found that 82 percent of organizations are worried about the escalating costs of building cloud analytic tools.

Data virtualization is something vendors have tried to do over the years, but it is very difficult to get right. Poor data quality, uncategorized and uncataloged data, and lack of data observability are just some of the roadblocks making it difficult to wrangle data.

Forrester noted that the vast array of data that businesses try to capture means that data originates from many different sources, causing businesses to cobble together solutions from different vendors. The Forrester report said that “this is in stark contrast to decades prior where just a single provider delivered most functionality necessary to manage data estates. Today, only 10% of respondents use different vendors for different use cases. Over the next one to two years, multivendor use will increase nearly four-fold to 38%.”