A popular game, now modernized via Facebook, is Where in the
World is Carmen Sandiego? You might ask the same of your SaaS
data. Where is all that highly valuable SaaS data when I need it? It’s
in the cloud but the traditional approaches to SaaS data access have made it
difficult, and time consuming to retrieve, and most importantly, to use the
data in up-to-the-minute analytics reporting
The
traditional approaches to data access have been the all-too-familiar
copy-and-paste CSV file shuffle, data synchronization or data warehousing. We’re
all familiar with the CSV shuffle -usually carried out as part of a last minute
dash to get a report delivered.
After
the CSV shuffle, data synchronization has been the prevalent means of managing
demand for SaaS data visibility. As the term suggests, it’s designed to keep
data replicated across various applications. It involves moving data
between two applications, such as adding an account to NetSuite when a
Salesforce lead closes. However, this approach has limited utility for business
intelligence and analytics since it limits the data available for reporting and
analytics.
Data
warehousing enables businesses to replicate SaaS data by moving it from the
cloud into an on-premise data warehouse, allowing users to build reports and
analyze data using their preferred reporting or BI tool. The
downside is you still have the challenges of maintaining the warehouse,
designing schemas for integrating data from various sources, and ensuring
freshness of the information.
Without
question, on-premise data warehousing is the most expensive, and time-consuming
method of SaaS data integration. It requires significant investment
in hardware, software and IT personnel. Even data synchronization
can quickly become a major IT project requiring weeks or months to implement,
without providing the flexibility to analyze and report on the data.
To take these SaaS data access issues for reporting and
analytics into the cloud computing era, we propose the concept of cloud
data virtualization whose foundation lies in standards based,
relational database technology. Cloud data virtualization frees you
from reliance on data synchronization and on-premise data warehousing.
Cloud data virtualization works by creating a virtual view of
data across multiple SaaS applications that appear to a user as a single table
from which they can instantly create reports and analyze data in their own
preferred reporting and BI tools. No longer do users have to implement data
warehousing or data synchronization projects that take weeks or months;
instead, with Cloud data virtualization they get access to their virtualized
SaaS data in minutes!
A
virtual table differs from a real data table in that the virtual table contains
“pointers” (called metadata) to where the real data is located. So
when a report or dashboard is generated using a virtual table, the cloud data
virtualization technology retrieves data from where it resides – in the source
SaaS applications – so it’s always the latest, freshest view.
Cloud
data virtualization works by using standard SQL, the language of relational
database technology, to translate the incoming SQL statements from a reporting
tools like Excel, Tableau, Jaspersoft, Crystal Reports, MicroStrategy, in fact
any ODBC or JDBC capable tool, into the language and functionality of the
underlying SaaS application. Think of it as a language ‘bridge’ from
your reporting and BI tools to your SaaS application data. This
eliminates the time consuming, and costly exercise of having to build or
purchase custom connectors and move data to a separate location.
With
the SaaS data access problem solved, cloud data virtualization offers up the
significant benefit of being able to access SaaS data from where it resides in
the cloud and build virtual views of data, saving you the interim steps of
moving data around your applications or into a data warehouse. The
data stays where it is, and can be pulled right into reports from any number of
popular SaaS applications such as Intacct, NetSuite, Zuora, Salesforce or
Zendesk. It gives business intelligence professionals the ability to
combine data from disparate sources, in real time – an ability that did not
exist before cloud data virtualization. The reports therefore
provide fresh data and are achieved without cumbersome interim steps.
The
cloud houses data that has been underutilized due to the historical roadblocks
caused by difficulty of accessing the underlying data. Add to that
the high cost of data synchronization and data warehousing and you can see why
SaaS data has not been leveraged to the fullest extent. With cloud
data virtualization, the data can remain in the cloud, yet be accessed in real
time, saving IT costs and enabling more powerful analysis.
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