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Data-as-a-Service: Dim Sum for Data

Joe Francica 

Senior Director of Geospatial Strategy

May 2, 2022

Data-as-a-Service: Dim Sum for Data

The confusing thing about data-as-a-service, or DaaS, is that there are so many different kinds from which to choose. There are the true data providers, some offering a data mart where you can view and download files directly (think, HERE Technologies’ Marketplace or Precisely’s Data Experience); cloud service providers (think, AWS Marketplace or Google Cloud) offering a hosting platform and access to data APIs; and then there are data platform providers, such as the Snowflake Data Marketplace, with their own unique style of a data marketplace. Each provider has a big enough portion of the solution that it looks like the entire meal, but you are likely to keep asking for more to be truly satiated. One provider may have a cloud data processing platform that offers speed or analytics; another is providing commercial data products such as demographics or digital map data. For best results, however, the solution cannot be an à la carte smorgasbord of data dumplings that leaves the user steamed. A solution provider that has the expertise to customize the technology menu to satisfy the entire banquet of business problems will likely be required.

Data is the New “Water,” the New “Oil,” the New “Bacon!”

Whatever analogy you use to describe the rise in importance of data, either from commercial or internally generated sources, organizations have placed data at the pinnacle of currencies in a digital-first world. Every company, no matter the industry, needs to think of itself as a “data company.” Data gathered from online or physical retail transactions and loyalty programs, for example, hold key insights into consumer preferences and expected market trends. Integrating disparate sources of data to establish inherent relationships that demonstrate buying patterns, trade areas, and merchandise demand is essential. These insights are particularly impactful to retailers, for example, as they try to maximize revenue on a per-square-foot basis. Likewise for transportation companies as they try to minimize fuel consumption for last-mile deliveries as consumer demand remains strong despite rising inflation.

Expanding the Definition of DaaS

Depending on the type of technology provider, the services that are offered vary, and defining DaaS is a moving target. Writing in Dataversity, Paramita Ghosh describes DaaS as follows:

The DaaS provider’s core competence lies in “curating, aggregating, and meshing” multi-source data to offer value-added intelligence or information. Typically, DaaS providers deliver “information” via a digital network, which is most often cloud-based. To this end, organizations may “buy, sell, or trade” soft-copy data as a DaaS service… Businesses of all shapes and sizes across the globe have suddenly caught on to the idea that DaaS not only promises unique revenue channels but also a path to “reshape the business world through competitive intelligence.

This is a much broader definition of DaaS encompassing a larger set of services than just providing a marketplace for data APIs. If data is now the lifeblood of organizations, then DaaS becomes a core competency that serves to deliver information on demand, in a form that is actionable. Let’s look at the broader list of services that help to define DaaS.

DaaS as a Marketplace

Daas as a Marketplace offers a choice between multiple vendors’ data products accessed through a web service or online eCommerce website. The user accesses the web service and purchases the data online. The delivery of data is limited to the format provided by the marketplace.

DaaS as an On-Demand Web Service

DaaS as an On-Demand Web Service offers a convenient and efficient way to get the data required for a specific business purpose in the format needed, on-demand, without the burden to download, process, convert, or integrate massive amounts of data, within the system of record. This personalized, value-added service can extract smaller (country, state, provincial or municipal level data), but unique regions (or lines or POIs) and be licensed accordingly. Data within those regions are also considered. The pricing model is transactional or consumption-based via a web service or API.

DaaS as Data Integrated into Application and Platform

SaaS mapping and analytics tools that allow users to embed data on-demand make it extremely easy to accelerate location analytics because of the ability to use internal and third-party data. In this model, data is integrated within the platform and accessible for consumption by the tool itself. The CARTO Data Observatory, ESRI Business Analyst, and Environics Envision are examples of this model.

DaaS for Advanced Data Delivery

DaaS for Advanced Data Delivery provides centralized procurement and sourcing from multiple vendors; pre-combined or conflated data sources; data integration and aggregation, with platform-specific delivery (e.g., Tableau, Microsoft Power BI, Esri ArcGIS Server, or ArcGIS Online, CARTO, Oracle Spatial MWM/OBIEE, SmallWorld, PostGIS, etc.)

DaaS for Automated Big Data and Data Ops Pipeline

This option refers to an end-to-end, fully automated data integration directly to the company’s environment or platform, so business teams can immediately leverage data. The process may be automated daily, weekly, or monthly as a cloud data delivery service (AWS S3, Azure Blob Storage, Google Cloud Storage); also cloud big data processing, aggregation, filtering with incremental updates and change detection; customer data contextualization; cloud data warehouse and feature store integration (e.g., Databricks, Snowflake, Google Big Query, AWS Redshift, etc.).

Geospatial Data Science as a Service

Geospatial Data Science as a Service process automation and/or modeling based on corporate needs and to provide teams with autonomy. Data processing may include data normalization, address standardization, geocoding, advanced geospatial modeling, and data dashboard development.

DaaS Consulting and Business Answers as a Service

Companies looking to leverage location-based data often don’t know where to start and don’t have the in-house expertise. These more advanced services are designed to help select data and convert them into business answers so that time-to-value is improved. Services may include data exploration, data sourcing, a location analytics pilot, data analytic services, and data business consulting.

To address the diversity of customers’ needs and contexts, the DaaS business model and offering need to include not only all the above but also Big Data as a Service where terabytes of mobile trace data demand processing power and checks on data quality. What many companies often fail to recognize is the complexity of enterprise use cases, especially when combining multi-vendor sourced data that may require their use by external parties outside of the core analytical tool, and therefore outside of what is permitted by the standard licensing terms. Whether it’s the volume of data or the licensing guidelines, companies are finding it increasingly difficult to navigate the DaaS model.

In a previous article that we wrote last year, The Rise of the Data Marketplaces and the Plight of Subway Sandwiches, we noted that there is any number of new data marketplaces looking to supply geospatial data in addition to those mentioned above. Data platform providers such as the AWS Data Exchange or Snowflake’s Data Marketplace now offer geospatial data products but without much support. And, lastly, there are pricing considerations. As mentioned above, slicing geographical data to only the area of interest, and providing it in the data format required by that company’s primary analytical tool is complex, especially when there are customizations that necessitate special price considerations.

Where’s the Gap?

Whether the user wants to access data from a data marketplace, an API, or a more traditional data catalog source, there is often a gap between the standard data product and a DaaS solution. From our experience, the gap usually consists of any of the following:

  • Customization of the geographic extents of the final product area
  • Technology gap needed for deployment
  • Expertise gap with geospatial data
  • Data engineer bandwidth necessary to improve time to value and to deliver the final product
  • Transparent licensing, terms, and conditions

Ultimately, the customer needs to create value from the data. As such, the complexity in understanding the way in which data can be purchased and consumed from each marketplace and licensed only represents the initial barriers. The challenges become more multifaceted as the needs of the organization expand to enriching corporate databases with additional attribution. At this point, they will begin to explore multiple data vendors perhaps even multiple DaaS marketplaces. The process of ingesting data from multiple sources (e.g., APIs, different data formats) and integrating them within an existing IT framework, and with specific infrastructure dependencies, adds another challenge. In addition, expertise in geospatial-enabling tools such as FME or Alteryx to support automated workflows, data updates, or geoenrichment (e.g., address validation, geocoding, spatial models) present special impediments.

Consider also when data are updated, or changes are made that impact geographic boundaries, points, or other location-based assets. Pricing and licensing terms may change. Each detracts from the ability to sustain business operations, adhere to service level agreements, and maintain regulatory compliance. Any changes that impact contractual agreements may have a material impact on the business and prior notice of changes need to be given.

This is where Korem’s unique personalized DaaS model and geospatial expertise support a client’s need for flexibility and agility to answer a variety of customer requirements. Korem offers five (5) key benefits for our clients:

  • Our extended, consolidated data portfolio, including more than 15 partnerships with some of the leading geospatial data vendors, and complemented by an internal market research team that understands the complexities of the market landscape;
  • Our core data-centric expertise in integration and data modeling;
  • Our advanced data transformation tooling combined with our technology agnosticism, allowing us to integrate with virtually any format and within any platform;
  • Our ISO-27001 certification and commitment to data security and data privacy;
  • Our complementary one-stop shop offers a contract advisory, centralized procurement, outsourcing and enablement, and data integration.

Every day, Korem is bridging the gaps between technology and expertise that support a shorter time to value. Our service is unique and personalized to the needs of clients that require an in-depth understanding of geospatial information.

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