Before we dive into DaaS (Data-as-a-Service), let’s take a brief look at the present and the past. Today, information is everywhere. It’s in our television sets, our personal computers, our cell phones and even our smart watches. 50 years ago, these technologies either did not exist or didn’t exist the way they do today. The 20th century brought with it many revolutionary new ideas and, more quickly than ever before, we continue to build on those ideas and develop new technologies.

Computers are constantly improving in terms of capabilities and processing speed. The information they process is valuable (think decision-making systems, analytics and metrics tracking) and must be collected and analyzed at ever-increasing speeds. This has then led to analytics becoming more prevalent.

Concepts like Big Data, Relational Databases, and Data Warehouses have become more commonplace as a result. However, as the internet has grown, relational databases have had trouble keeping up. They can’t seem to handle the large volume of information coming in, nor the combination of data from multiple sources. This led to the concept of a data warehouse. The data warehouse made it easier for the end user to understand the big picture of their data by merging many database layers together into a single record system. This allowed applications like Business Intelligence and Big Data to flourish.

The Rise of DaaS

At this point in time, we had the ability to collect data easily and store it in a way that made sense. We could analyze, calculate, and make predictions based on the data collected. So, what was missing? All this data was still being stored locally and costing organizations thousands of dollars each year to maintain. Organizations had to hire large IT departments to manage the hardware, infrastructure, storage, and distribution of their data. There had to be a better way.

Along came Data-as-a-Service.

Data-as-a-Service, also known as DaaS, is simply “an information provision and distribution model in which data files are made available to the customer over the internet.” For example, Organization A stores data for Organization B and makes it available over the internet. This is a much simpler way for Organization B to alleviate the rising IT costs mentioned above. DaaS is an enticing option for any medium-to-large sized organization.

How it Works

A traditional DaaS setup works like this:

1. Organization B takes all its data and uploads it to Organization A
2. Organization A places the data into a data model (as specified by Organization B) for storage
3. Organization A delivers the data via APIs or other interfaces to Organization B

Benefits of DaaS             

Some of the benefits of DaaS include:

• The reduction of IT costs and resources needed to manage the data
• High availability of the data, on multiple platforms
• Single source of truth
• Offload the burden of data management

Risks of DaaS

Just like any new technology, DaaS doesn’t come completely free of risk. Some risks of utilizing DaaS include:

Privacy

Any time data leaves the organization’s firewall, security becomes the primary concern. DaaS is no different. Remember that other organizations also store their data with your same DaaS provider. In most cases, do your homework on any DaaS vendor and select the one that alleviates your security concerns the most.

Data Governance

Most organizations with an ERP system understand that data governance is no easy feat. DaaS doesn’t automatically ensure that data governance is in place. You must establish that first, before you can effectively store your data in an easy-to-manage way via DaaS.

DaaS and Higher Education

The higher education space is no stranger to large amounts of data. There is a need to extract data from ERPs like Banner and Colleague, and web data sources like Canvas LMS, Slate, Salesforce, etc. With the increasing number of data sources to manage, it can be a huge effort to join these sources together for any sort of reporting. This is where DaaS comes in. With Data-as-a-Service, multiple data sources can be streamlined into the established data model. This, then, allows the data to be joined together easily.

Data-as-a-Service is still relatively new in the higher education industry. Many institutions today are already familiar with cloud storage and controlling their data as if it were stored on premise. (A cloud strategy is becoming more common for primary SIS data sources.) DaaS takes the next step and combines the data into a consistent structure. This makes it easier for an institution to use the data for business intelligence, analytics and visualizations.