SaaS BI delivers business intelligence solutions as a cloud-based service rather than an on-premise installed software. It provides benefits like lower upfront costs, easy scaling, and mobile access. Key aspects of SaaS BI include subscription-based pricing, software hosted remotely and accessed via web browser. While it improves accessibility, SaaS BI tools may have fewer features than on-premise options and raise data security concerns. A case study found that a trade group was able to simplify report distribution and lower costs using SaaS BI compared to traditional on-premise software.

1. Software as a
Service BI (SaaS BI)
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-Anushree V. 1627035
-Vedant Somani 1627337
-Souparno Basu 1627128
-Akhil Jose 1627303
-Ranjith M 1627019

2. WHAT IS SAAS?
• A way of delivering solutions over
the internet – as a service.
• Instead of installing and maintaining
the software at your own
organisation, you simply access the
solution online.
• Sometimes called as on-demand or
Web-based software.
• All solution updates occur
automatically.

5. Business Intelligence (BI), until recently
was largely confined to larger enterprises
because of the high capital expenditure
involved.
Smaller and medium businesses (SMBs)
had to rely on tools like spreadsheets for their
BI requirement needs.
All this has changed with the arrival of
SaaS BI - BI delivered as software-as-a-
service.

6. What is SaaS BI ?
• Delivery model for Business Intelligence.
• Applications are typically
deployed outside of a company’s
firewall at a hosted location.
• Accessed by an end user with a
secure Internet connection.
• Also known as on-demand BI or cloud BI.
• The technology is sold by vendors on a subscription
or pay-as-you-go basis.
• Not as a traditional software licensing model with
annual maintenance fees.

7. BENEFITS
SaaS BI and the cost of a single user
• SaaS BI offers one significant benefit over
on-premise applications: they are much
easier and more cost-efficient adding users
to the application, whether you are adding
1 user or 1000 users.
• For example, adding a single user to a
SaaS dashboard means paying for an
additional "seat" and supplying that user
with credentials for accessing the dashboard
using a web browser. On the other hand, adding a user to an on-premise
BI application requires installing the software on the local computer,
potentially upgrading the computer, and then synching the application
with other computers on the network.

8. SaaS BI and accessibility
• SaaS BI also offers the advantage of accessibility.
• Unlike on-premise applications, which may be
locked behind a firewall, SaaS applications can be
accessed on any device with an internet connection.
• Not only is it easier to view
information, such as data
dashboards, with a SaaS BI
application, it also makes the
application easier to deploy
since it only requires a
web-browser (no upgrades or
software installation needed).

9. SaaS Dashboards: The expression of
BI in the Cloud
• SaaS BI offerings include multiple types of
applications; however, SaaS dashboards may be the
ideal expression of BI in the cloud.
• The reasons for this is that dashboards summarize
and consolidate key facts about the business for easy
consumption.
• By deploying a SaaS dashboard, enterprises can reach
a large audience quickly
and effectively encourage
users to view business
critical information during
the course of normal
web-browsing.

10. Leveraging the Already-Collected
Data
• Even though most companies go out of their way to
gather as much data as they can, most critical data
doesn’t even get used.
• In fact, researches have revealed that between 60 and
73 percent of data goes unused for business
intelligence analytics.
• With an increasing number of smart devices,
collecting large amounts of data is not a problem
anymore.
• However, it is not easy to get that data in a suitable
format that companies can work with, and data means
nothing if the right technology is not applied to it.

11. Analyzing and Understanding the
Customers
• Collecting all of the information and compiling
it in a meaningful way will definitely help any
organization understand customer behavior and
enable the marketing department to target
their efforts to a specific customer
demographic at specific times.
• Data-driven decisions can also help companies
forecast the effectiveness of certain marketing
campaigns before they are even launched.

12. Gaining a Serious Advantage Over
the Competition
• Data preparation is quickly becoming a critical
capability of experts, who traditionally relied on
others to get the data sorted out and ready from
them.
• In order to transform unsorted data into
information on demand, people doing customer
targeting, risk analysis and marketing operations
will need the necessary tools and skills to handle
self-service data preparation at scale.

13. TRADITIONAL BI IMPLEMENTATION

16. ISSUES WITH SAAS BI
• The analysis tools may not have all the
features that on-premise software products do
– which may make them less complex and
difficult to use, but also less functional.
Sending corporate data beyond the firewall
also raises red flags for some IT managers.
• To try to assuage those concerns, some
vendors have created private analytic clouds
that run inside a customer’s firewall.

17. • Customers are essentially renting, not
building, the software - and it’s usually the
software rather than the platform or the
infrastructure - they need to define their
requirements up front.
• That might work for CRM but presents a
challenge when it comes to BI.

18. • BI is different from any other enterprise
application because BI is not an application;
it’s an environment that often changes on a
daily basis.
• Having control over that environment is
very important and challenging.

19. • While a cloud-based BI application may be
a good option for smaller businesses, the
challenge facing larger companies is data
integration: Combining sales, financial,
point-of-sale and social media data across
the enterprise for a unified, complete view
of the business.

20. • Data security concerns are one potential
roadblock to a brighter future for SaaS BI.
• Vendors also continue to face questions
around the maturity of technology for
integrating cloud BI tools with data
warehouse systems and other data sources
residing inside corporate firewalls.

21. A Case Study: Pandora Media
• Internet radio company Pandora Media is
using Software as a Service reporting tools
from BI vendor GoodData to analyse its own
site-usage statistics and rankings
information from external data suppliers.

22. • At the Association for Manufacturing Technology (AMT) in McLean, Va,
a SaaS Business Intelligence system deployed has simplified the process of
distributing reports and BI data to the trade group’s members.
• The cloud BI tools have also been much more economical for the association
than investing in on-premises software, new hardware and internal IT resources
would have been.
• In particular, business intelligence in the cloud gives the AMT to ability to
scale the BI System up or down as needed without requiring substantial
investments or creating an administrative burden for the group’s IT staff.

23. SaaS BI Vendors
• IBM Cognos Analytics
• Microsoft Power BI Pro
• SAP Business Objects BI
• Birst BI
• GoodData
• Indicee
• Kognitio
• Pivot Link

24. The Future Trends of SaaS BI
• SaaS BI usage will grow faster than traditional on-
premise BI applications.
• Managers and Self-employed business people will be
the fastest growing segment of the SaaS BI users.
• Analysis or Reports without Benchmark will not be
credible.
• The Definition of “Send me” a report will change.
• Price will drop, barrier to entry will be lowered and
ease of use will be the difference between winners
and losers.

25. And Their Reasons….
• Storage is becoming cheaper in the cloud, and the
business only has to pay for what it uses.
• The second factor is processing power: processing
also costs less and is more flexible.
• Thirdly, there are more cloud-based tools in the
market that allow you to read across the data, or
carry out processing. The cloud is allowing
companies to do analysis that was previously not
economical.

26. References
• http://searchbusinessanalytics.techtarget.com/definition/So
ftware-as-a-Service-BI-SaaS-BI
• https://www.klipfolio.com/resources/articles/what-is-saas-
business-intelligence
• Case Study :
http://www.computerweekly.com/news/2240101895/Cloud-
analytics-the-future-but-not-today
• http://bigdataanalyticsnews.com/business-intelligence-
analytics-is-the-future-of-saas/

27. THANK YOU