Why Venture to Cloud Based Business Analytics

A Position Paper Citing the Development of Cloud-Based Business Analytics

A partial fulfillment of requirements for

MIT Specialization 4

Submitted by:

Michelle Anne L. Constantino

G22

Submitted to:

Ms. Amy Lyn M. Maddalora

Professor

Revision

Nowadays, battle between providing services has always been with

on-premise servers vs. the cloud-based environment. There are

differences in both types of servers with one being owned and the

other being a part of a number of virtual servers that play host

to various companies that are considered to be a boom because

they are much scalable or they would not need to acquire too many

resources. The focus of this position paper is to talk about why

people should start moving to cloud-based business analytics in

the foreseeable future and how being in the cloud revolutionize

the game of business analytics.

Gartner defines Business Analytics as “solutions used to build

analysis models, simulations to create scenarios, understand

realities and predict future states”. Business Analytics

erstwhile have three types: descriptive, predictive and

prescriptive which are all invested on by a company. Mckendrick

(2012) mentioned in the article that even as businesses and IT

spending go down, companies still invest on BI and analytics

itself since the value is expected to reciprocate itself over

time.

On-premise business analytics are still common with the entire

data still being built on a database server with resources being

maintained by in-house IT personnel meanwhile cloud-based

business analytics are a part of the cloud paradigm which deploys

solutions over the internet.

Analytics within cloud computing has not been implemented by most

of the companies, there is still an issue on the use of cloud as

a service with security being its main consideration since

companies will not own the resources, they would be riding on the

service of the cloud provider and will not see the internals on

how does it operate. There is also a discussion on to where the

data will be placed into since building cloud-based business

analytics removes the idea of having your own database server

within your reach thus moving everything to the cloud.

Cloud-based business analytics had been introduced in Technology

articles around 2011 and is seen to have to boom in 2-3 years

time. In the advent of big data and the need for space to conduct

business analytics, cloud may seem to be the best solution even

with the loopholes that needs to be addressed.

Many of those who got the idea of conducting cloud-based business

analytics may seek the following reasons:

Company Stability

Companies or SAAS (Software-as-a-Service) providers have

provided the same kind of service and some of them had not

compared well yet to tech titans which are selling on-

premise business analytics software, there is still doubt

that when a company avails cloud-based business analytics as

to how long they would be capable to deliver the service you

requested, not unless if they are a company like IBM which

had established its name towards its software deployments,

there are still questions on how this new cloud business

solution players are working to be able to achieve their

goals.

On-premise based analytics software are lucrative when it

comes to their functions compared to on-demand business

analytics where they seem to look like to be to good to be

true.

Security

Placing a data warehouse within the cloud opens up the

company to losing information over the internet, unlike in

an controlled setup like the data center, data is meant to

be accessed by individuals who are given the access rights

to the database, thus when they perform on-premise business

analytics, there is an assurance that what they are able to

see is something that they have the right to see.

Cost

When it comes to moving to cloud-based business analytics,

migration of data with what ordinarily has been within on-

premise is subject to cost and if you are moving to another

software, it would be asked why do you need to change when

you have with you the king of BI applications, Microsoft

Excel. Sherman (2010) of Forbes believed that to be

successful with cloud-based BI, one must be able to knock of

at least the king of its throne.

Redundancy: What if cloud based solution provider for

analytics fail?

Most cloud based solution providers have in their quotations

the term they do the backup for you and had provided a

measure wherein your backups storage are in place. However,

every minute that is down is every minute of lost within the

company. What if you want to generate a report on a certain

degree of sales measure then find out that your cloud server

is down.

The concept of redundancy is still available on on-premise

servers with a physical and a standby server intact. You can

have your servers up in no time.

The picture above is an example of an Oracle DataGuard setup

which is used in companies where a primary server and a

standby server are together setup. The primary server is in

sync with the standby server by sending the archive logs or

the changes that occurred within the primary database. In

the event that a disaster happens, the database

administrator or whoever is in charge of the database

services can perform a series of queries to switching the

database to declaring that the database needs to be switched

or there is already a failure in the instance and one must

be needed to come up. There is also a redundancy procedure

that can be done within the cloud but should be taken into

consideration strongly.

Another reason why companies (or service providers) do not

venture totally to doing cloud-based analytics is because

the cloud is not meant for redundancy, the best thing they

can actually do is to have a backup copy of your data –

physical copy. It is not the same as on-premise servers

where what you have is something you control of using.

Why go Cloud Based Business Analytics

Company Stability

Companies that are selling on-demand BI applications are

still around because they cut costs implementation, make do

with the scarce resources and make it easy for their trained

users to get to know their applications. Their portability

and availability makes them still stand even with the

competing brands they have today.

Security

Liberman Software (2012), one solution provider for cloud –

based analytics defines the need to have privileged identity

management of the software, they had established ERPM or the

Enterprise Resource Password Manager. ERPM automatically

discovers the privileged accounts that could be able to

access the network. . It helps protect an organization’s

most sensitive data by fully auditing administrative access

to systems and applications in the IT infrastructure. ERPM

specifically shows who had access to systems with critical

data, at what time and for what stated purpose.

Cloud based service providers also has the control of the

remote access to the IT infrastructure and would be hard to

bypass if done outside the network.

Cost Extensibility

Depending on the type of service and the extent of coverage,

cloud based analytics may turn out to be expensive at first

but later on, you would realize that the infrastructure

would actually last longer compared to having your

applications hosted in an on-premise infrastructure.

Investment-wise, having to go for anything cloud-based may

seem to be appealing than to upgrade every now and then, you

maximize the ability to scale up and to grow with your data

when you are in the cloud.

Redundancy

Cloud based solutions keep a copy of the backup into RAID

formats that they use in case of failures.

Performing Cloud Based Business Analytics

Klipfolio defined cloud-based BI as a series of applications that

are hosted in a virtual network such as the internet. Cloud-based

solution providers can handle the complexities of implementing BI

– from assembling the analytics components, networking and

storage plus data normalization through ETL, management of data

sources, and finally, achitecting of an analytic solution by data

scientists and analysts.

Figure 1: ETL Processing

This figure explains what a data mart ETL process contains which

refers to a process in database usage that: extracts data from

outside sources, transforms it to fit operational needs and loads

it to the end target. The figure also notes that throughout the

process, security and data privacy as well as systems management

and administration must be taken into consideration.

Gadhi (2011) mentioned that transformation to cloud computing

changes the economics of business intelligence and analytics.

Cloud computing is both a business delivery model and an

infrastructure management methodology. The business delivery

model provides you with a standard offering of services, such as

business analytics that are easily accessed and rapidly

provisioned. Steps, such as producing hardware, installing

middleware and software, and provisioning networks, are

dramatically simplified. The infrastructure management

methodology is built on virtualized resources and provides better

economics and increased ability to scale. It makes high-volume,

low-cost analytics possible.

(Gandhi, 2011) Not all clouds are created equal there are still

differences on important attributes such as location, ownership,

access, targeted users and workload (application types), varies across

an array of clouds. The picture below describes the types of cloud

services you can choose from:

Figure 2.0 If you are going to look at types of cloud-based services

which are available within the market, it concentrates to 3 standards:

private cloud, hybrid model and public cloud. A private cloud is

dedicated to an enterprise behind the firewall. You could also use

subscription services that will just host the server for your company

and not share it with others. A public cloud is a series of IT

activities/functions that provides a virtual server to a number of

companies while a hybrid cloud is something that may instantly be

taken into consideration as it does not eliminate the internal servers

(database) while starting to move some services into the cloud. The

three types of cloud meant to augment what traditional IT

infrastructure has which is behind an internet, within the enterprise,

manned by an IT personnel that develops/maintains the system.

Companies Doing Cloud-Based Business Analytics

Tibco Jaspersoft, a provider in Cloud-Based Business Analytics has

tied up with Amazon Web Services to provide cloud-based services that

serves startup companies to the Fortune Top 500 companies they provide

the service payment for an hour for as low as $1 or an annual payment,

consuming the service you only use.

Haidar Hadi, programmer for Devicescape likes the idea of this cloud-

based analytics providers that they were able to finish their

deployments and install their dashboard in less than an hour

instantly. Jaspersoft has tried to meet the needs of their clients

with its partnership not just with AWS but with other major service

providers such as Red Hat, Microsoft, etc.

Other companies performing cloud-based business analytics are also

around to venture into the service and others like IBM, Bodais,

Alterix, Kognitio etc.

Why venture to Cloud-Based Business Analytics anyway?

There’s always the question of security or who’s who within the

companies that offer the same kind of services within the

provider, but still cloud-based business analytics has shown a

lot of promise on why companies should start venturing into the

process.

Below is a reason for SaaS Adoption as studied by Gartner (2012)

which is why companies had adapted cloud-based business

analytics.

The figure above represents Gartner’s study on the Primary

Reasons for Driving SaaS Adoption for 2 years (2010-2012) where

the primary force of the adoption of SaaS based on percentage of

respondents is the perceived lower total cost of ownership (TCO)

than the on-premise solution.

Another study made by Nelson (2014) cites a research which

includes the following figures:

Key findings include:

54% of IT leaders would choose a cloud-based BI solution for

a new environment, against just 14% who would prefer on-

premise

80% of those who choose cloud BI are satisfied with their

service, versus only 51% who are satisfied with their on-

premise solution

Cloud has a definite speed advantage: 83% of respondents say

they can implement cloud BI faster, against only 4% for on-

premise

Cloud also has a cost edge, with 68% of cloud BI

implementations coming in at, or below, expected costs,

while 54% of on-premise solutions met their cost

expectations (this means nearly half of on-premise

implementations exceeded cost estimates)

44% said on-premise requires more user training, versus just

5% who think cloud needs more training for employees to

learn

On-premise solutions also lag behind in frequency of use,

with 51% saying that cloud BI is accessed more often by more

employees, against just 18% for on-premise

Predictably, not one respondent said on-premise was better

for mobile accessibility.

Cloud-based business analytics does not take away jobs, they make

the job easier for the employee who had been doing the report or

does adhoc reporting. If you were to talk about having to scale

up, work with data marts that store at least 15 years or data or

analyze a current situation based on what is requested, then

cloud based is the name of the game for business analytics.

Cloud-based analytics has run into the minds of various organizations

as a cost-effective way of providing solutions for the generation of

reports, analyzing data and to make decisions onto the level of the

top management. There is also the thought of scalability: How much

data are we going to have in 5 to 10 years from now and how do we do

capacity planning.

However, the implementation would require indeed a serious study as to

the following reasons:

Do we move everything to the cloud as quickly as

possible?

What do we do on-premise? Do we do parallel analytics

with the resources the company has?

The security level? How do we make sure that it is

safer even if we do the analytics outside the cloud.

The idea is no longer foreign, since companies and decision-makers

would look at their equipment long term, going cloud-based, which

would mean having to rely on virtualized solutions means addressing

the need of buying that much infrastructure or worrying about

compatibility issues. There is also such a thing as “trial period” for

software that provide cloud-based solutions, you can try and remove

the virtual machines you’ve captured after a month which makes cloud-

based solutions appealing to individuals and companies as well.

Reports show that cloud-based solutions may not be as popular now

since a handful of companies had just started using cloud-based

business analytics but would definitely grow in 2014. With the advent

of development of big data, analytics is meant to be hosted in a

platform that actually scales up as you need it. Data is Wealth, and a

company with that much data can use it for bigger situations or tasks

at hand. For now, we are here to witness the development of cloud-

based analytics, from PAAS, SAAS and other BI applications which help

make decision making easier.

The proponent of this position paper entitled: Why Venture into Cloud-

Based Business Analytics provides plan of action towards implementing

cloud-based analytics, to which experts may look into when building

their data warehouse soon:

Take advantage of the cloud based business analytics

solution providers which wants to let you try their

services – at least you would not commit instantly

without knowing the specifications of the cloud-based

services. There is also the per hour approach such as

the one provided by Jaspersoft where you only pay per

hour of the services you need with the same service as

of the annual price.

Identify what can be taken out and what should be left

within your reach – Data yes, you would have to work

with it but you cannot really put everything up there

in the cloud until you are sure of it.

Migration will never be easy – you cannot do away with

your on-premise infrastructure just yet. Data to be

migrated should be looked into, extensive

transactional data must be kept on an on-premise

server. Know what to put out and know what stays.

Do capacity planning – Cloud is scalable, but it does

not mean you should immediately go 2TB HDD. Capacity

planning is required to know what kind of cloud

solution should you need to set up, the processor, the

RAM and the HDD so you would utilize the service

properly.