Data access is a critical factor in adopting SaaS solutions for organizations, and the Salesforce developer evangelists that sponsored my Dreamforce session last year shared that data connectivity is the most popular topic on the developer track.
Michael Biddick, CEO of Fusion PPT and contributor to InformationWeek, recommends getting senior executive support and involvement to understand SaaS data access strategies to avoid surpises. He shared, "data ownership is also a big obstacle, with 31% citing it as a reason they're not using SaaS.". Concerns like these can be mitigated with a comprehensive data access strategy.
Let's take a closer look at how data access strategies impact organizations. Using my experiences as the world's leading consultant on direct SQL integration with SaaS, I have built a visualization contrasting the different strategies with data collected from our user base. In addition, I will expand on each strategy with specific feedback on challenges that we have solved that would otherwise block adoption or renewal.
SaaS data access strategies contrasted with direct SQL Access
This approach is the solution to ALL the blocking objections we have seen for adopting SaaS solutions described in the article, and should be part of every SaaS data access strategy. End users, consultants, system integrators and SaaS vendors have all shared countless instances where our connectivity either enabled adoption, expansion or renewal of an annual subscription. DataDirect has been building secure and direct SQL access via ODBC and JDBC to multi tenant SaaS sources since 2006.
The data export is definitely a first step in sharing SaaS data. Even with good intentions, it can get pretty ugly for certain shops trying to perform common tasks. For example, the illustration below describes the current pain of a shop trying to supplement SQL capabilities from a data export for daily updates. And this is limited to a single table, and must be done when users are offline to avoid overwriting updates since the data becomes stale upon export.
I really felt bad for these guys.
Gadi Yedwab, CEO of Explore Analytics, shared the challenges with analytics from web services since they lack a standard expressive query language:
In addition, SaaS vendors may count on third parties to build application specific integration that typically becomes stale over time. These one off adapters are written to different levels of your API providing inconsistent views of the data, or making the application unusable. For additional comparison of SQL access versus web services, check out my previous article.
SaaS vendors may coordinate with third party vendors to stage tables from their application to a relational database. The collective concerns I hear include:
This approach, along with the data export, do not offer right time capabilities. An example of a show stopper for adopting a hosted solution is from an organization making decisions based on real-time OBIEE dashboards that are integrated into their work flow that run the core business. Ultimately, they were able to move forward by using a real-time ODBC driver from DataDirect. Operational business intelligence is a growing requirement for SaaS vendors and their cloud platforms are highly capable of delivering with a direct SQL interface.
Integrated intelligence may be provided by SaaS vendors via home grown reporting within the application, or hosted solutions such as IBM Cognos, SAP Business Objects, etc. I completely support this capability for SaaS data, however it should not serve as the data access strategy. I have seen a lack of direct SQL access from ETL/data integration platforms block adoption by large enterprises and organizations with sophisticated intelligence requirements that require 360 degree intelligence beyond the SaaS data.
The most common corporate standard platforms typically run Informatica, DataStage, or Ab Initio; along with SSIS, SAP Data Services, Talend, Oracle Data Integrator or Pentaho Kettle to name a few. Your data needs ODBC/JDBC access for integration across all these platforms within the organization.
Internally, we have adopted several SaaS solutions. Examples include CRM, marketing automation, and compensation. Recently, my team started working on a scorecard for the executive team; and our BI platform is ODBC based. Since the CRM is Salesforce and there is a real-time Salesforce ODBC driver, it was decided to build custom integration to push data from marketing automation into Salesforce.com; and then connect into Salesforce via ODBC from the BI platform. I had no idea how to get data out of the compensation package, so I just gave a REALLY LONG estimate for completion and they decided to go without it (brilliant!). Guess what data our executives will see and which of these solutions will be easiest to switch out come renewal time?
Progress DataDirect offers the following solutions to SQL enable SaaS:
Or call us at 1-800-876-3101 to speak with a Systems Engineer for consulting on the best data access strategies for both your current and target user base.
Sumit Sarkar is a Chief Data Evangelist at Progress, with over 10 years experience working in the data connectivity field. The world's leading consultant on open data standards connectivity with cloud data, Sumit's interests include performance tuning of the data access layer for which he has developed a patent pending technology for its analysis; business intelligence and data warehousing for SaaS platforms; and data connectivity for aPaaS environments, with a focus on standards such as ODBC, JDBC, ADO.NET and ODATA. He is an IBM Certified Consultant for IBM Cognos Business Intelligence and TDWI member. He has presented sessions on data connectivity at various conferences including Dreamforce, Oracle OpenWorld, Strata Hadoop, MongoDB World and SAP Analytics and Business Objects Conference, among many others.
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