Business Intelligence Using Big Data

Business Intelligence is a new business exploiting technology, implemented today by not only large scale businesses, but also medium and even reaching small scale businesses, technically. Among various technologies and tools for visualization of the extracted data, from big data, the best tool and architecture are needed to be selected and implemented for the best outcome.

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BUSINESS INTELLIGENCE USING BIG DATA
DATABASE
6/5/2019

EXECUTIVE SUMMARY
Business Intelligence is a new business exploiting technology, implemented today by not
only large scale businesses, but also medium and even reaching small scale businesses,
technically. Since there are more and more technologies and tools are developed every year,
there needs an additional effort for the project managers to choose the appropriate technology
and tool suitable for the respective business case. Business Intelligence enables the
businesses to exploit the data, as never before and today businesses do not need much time to
reach the anticipated levels in the business and achieve the business goals in shorter
durations. Among various technologies and tools for visualization of the extracted data, from
big data, the best tool and architecture are needed to be selected and implemented for the best
outcome.

Contents
INTRODUCTION.....................................................................................................................................3
BIG DATA USE CASES AND CRITICAL ANALYSIS OF BIG DATA TECHNOLOGIES.......................................3
TABLEAU............................................................................................................................................3
Differentiating Features.................................................................................................................3
Feature..........................................................................................................................................4
Usability.........................................................................................................................................4
Pricing............................................................................................................................................4
TABLEAU ARCHITECTURE...............................................................................................................4
PROS..............................................................................................................................................4
CONS..............................................................................................................................................5
QLIKVIEW...........................................................................................................................................5
Basic Features................................................................................................................................5
Usability.........................................................................................................................................6
Pricing............................................................................................................................................6
Summary.......................................................................................................................................6
Differentiating Features.................................................................................................................6
POWER BI..........................................................................................................................................6
Features.........................................................................................................................................7
Usability.........................................................................................................................................7
Pricing............................................................................................................................................7
COGNOS ANALYTICS BY IBM..............................................................................................................7
Functionalities...............................................................................................................................7
BIG DATA ARCHITECTURE SOLUTION....................................................................................................8
Business Strategy...............................................................................................................................8
Architecture.......................................................................................................................................8
CONCLUSION.......................................................................................................................................10
REFERENCES........................................................................................................................................10

INTRODUCTION
The advancement in technology today has provided a long list of powerful Business
Intelligence tools and Data Visualization tools, which enable to illustrate the new ideas,
visualize huge data, interact with it, and share the analytics with the global community and
customers. The list of Business Intelligence and data visualization tools is huge, today. These
tools basically help in illustrating the intended idea, visualize the required data, interact with
it, share the analytics of this huge data with the global community and clients of the business
(Coker & Frank, 2014). Since the list is very long, the most commonly used platforms tools
are addressed. To explore the real time usage and variations in functions, it is important to
explore more in terms of functional product value of the tool. It needs to explore primary
features, special features, cons and pros of the most commonly used tools.
BIG DATA USE CASES AND CRITICAL ANALYSIS OF BIG
DATA TECHNOLOGIES
In this telecom project, the basic use case is to analyze the customer, analyze the network
traffic and improve the business and eventually profits.
TABLEAU
Tableau is one of the biggest players in BI. The tool allows data dashboards creation and
distribution in easier way and allows an insightful dynamics depiction, data density
distributions, trends of change, through simple yet effective convenient medium visuals. The
tool facilitates connecting to data of multiple types and sources, with several systematic
types, like data in various file formats, like MS Excel, XML, JSON, CSV, etc., various cloud
systems, like Oracle Cloud, AWS, Microsoft Azure, Google BigQuery, etc., and data
systems, both relational and non-relational, like SQL Server, PostgreSQL, MongoDB,
MySQl, etc.
Differentiating Features
The most differentiating feature of Tableau architecture that makes him stand apart from it
competitors is the special data blending feature. One more feature unique to this tools is the
collaboration ability in real time, allowing it as a valuable investment for the organizations,
no matter non-commercial or commercial, in the same way. The reports of Tableau can be
shared in various ways, via tableau Reader capability of email, via publishing the reports to a
Tableau server, through openly publishing its workbook and allowing access through the link.
These numerous options removes various restrictions and enables the users of Tableau, a
great flexibility. This is the major benefit and reason for choosing Tableau architecture for
this telecom project.
Tableau offers visualization capabilities in a broader variety, with distinct features and allows
deep insight and data discovery to be done in smarter ways. It contains rich visualizations
types library that includes ‘bubble charts’ and ‘word clouds’, which provide comprehension
at higher level and this feature is unique to Tableau. Its treemap helps for depiction of
categorical data parts with more focus on the information that is most relevant.
Dashboards of Tableau are flexible, amazingly. Its basic and central feature enables the user
to layout the dashboard, remarkably, in the way designed with handy overlaps that is very
handy in the ergonomics of screen space.

Tableau architecture allows apprehending as a good working tool, because of its pretty gentle
learning curve. It also allows all the power to provide to all kinds of users, even without
technical aspects of workflows of visualization. It is made possible through intuitive interface
and enables any task is made possible with just two clicks nearly, drill downs that can be
found and used easily, easier robust filters. The best part is that the operations are labelled
and documented well.
Tableau is pleasant and very easy to use in perspective of developer however, the user can
control the outcome, through customer parameters set with additional filtering. Data is very
well communicated in an attractive, clear and interactive ways. The tool offers look
insightful, at the data and enables the user to compress the process of complex decision
making, very efficiently.
Tableau tool is notable for variation with wider and myriad of choice and great flexibility for
sharing of data. A proper solution can be surely obtained by even the pickiest users and
enables it to satisfy most capricious needs of them.
Feature
 Support for cubes
 Ability of complimentary sharing, though with some limitations
 Mixing various sources of data
 Supports to connect to more than thirty data source types
 Leadership with efforts in community building,
 Ready-made drivers mapping made for multiple databases by integration with R
Usability
Ease of use experience is extraordinary for the user and so Tableau stands as the best easy to
use tools. Considering this feature, the use case, most convenient to it is the structured data
discover through graphs, charts and many kinds of visualization. Casual business users can
also use it to get the reports very easily. For them, building attractive visualization, importing
data, sharing and publishing data and visualizations are easier and straightforward. Other BI
solution tools, like Qlikview, Power BI from Microsoft and other IBM product cannot make
it easier than Tableau, enabling great power to Tableau’s users. This is the reason for
choosing and using Tableau architecture for telecom project, rather than other architectures.
Pricing
Tableau is available to the users and businesses of different scales, as it offers three distinct
prices for three distinct products Tableau server, Tableau online and Tableau desktop.
TABLEAU ARCHITECTURE
Tableau is an n-tier client server architecture, which is highly scalable. This big data
technology serves web users, mobile users and also desktop installed software.
PROS
 Attractive and intuitive user interface
 Provides extensive native data connections roaster that allows many sources to
integrate with data, easily
 Well supported by mobile platforms with better responsiveness

 Seamless integration with Google BigQuery from Hadoop and many modern big data
platforms
 Regularly released developmental features and are constantly developed, releasing
new updates
 Reliable customer support
 Powerful collaboration of community
CONS
 Demands IT consultancy support, especially, while using Tableau server
 Restricting and specialized features, though, intended to have users broadly
 It needs initial preparation or structurization of data
 No versioning concept with Tableau server
 Enables to establish security at row level at the level of data, however, bit precarious
way implementation
QLIKVIEW
Qlikview has a major focus on the user, as a data receiver and provides solutions relevant to
the same. This tool enables simple users to explore and discover the workflow data, as the
developers do work, while processing the data. The tool strives to maintain data association,
to sustain flexibility for exploration and visualization of data. It also facilitates the data
discovery through seeking specific data pieces, by the end-user, being aware of any relevant
items retrieval, besides any kind of circumstances, though the items’ origins applicable to the
search are disjoint, incredibly.
QlikView is very flexible and allows tweaking and allowing every smaller object’s aspect
and customize visualizations and dashboards with customized feel and look. The tool
incorporates an Extract Transform, Load engine that allow conducting ordinary operations of
data cleansing. However, the major issue with this tool is, it is costly.
Basic Features
Qlikview has a decent combination of flexibility and uniqueness and so has a good number of
applications in multiple industries and businesses of different scales. It enables the users to
create advanced dashboards according to data collected from various sources. The tool can
automatically perform data associations and manipulation and recognize data items
relationship in one dataset, having no user’s explicit pre-configuration. Eventually dashboard
development process gets speeded up.
One more feature is the way data input is handled by the user, through placing the data in
RAM memory of the server, thereby allowing quicker exploration of data, through faster
queries. Eventually, calculation of aggregation becomes faster, rather than pre-computed
querying of aggregated values. So, the tool is memory-efficient.
The formidable advance of keeping data in memory demands more RAM volume and this is
an issue. It resolves to some extent by minifying the data for about 10%, by compressing. It
needs heavy data dictionaries usage and using the essential data piece only for analysis.

Usability
The reports and dashboards of Qlikview are easier for navigating, even by novice users. But
building reports is quite challenging, as it demands default SQL proficiency, higher level
skills for developer and intense training for database interactions building.
Pricing
Qlikview stands as a platform in the field of BI that is one of the most expensive one and
policy of pricing is confusing and complicated.
Summary
So, Qlikview enables the user to build an appropriate solution, only with right mindset in
terms of programmatic interface application along with integration of right questions,
especially, when data is sourced from multiple sources. It needs additional efforts for proper
reporting maintenance.
Differentiating Features
The major differentiating feature with competing products is that it helps to reproduce most
of the features of it, in most cases, unsuccessfully. It is a major disadvantage. Qlikview
design is done on the basis of applications of avant-garde prebuilt dashboard and associative
dashboards, which are intuitive and innovative for using. It also enables the need of pulling
data in-memory and data warehouses, using associative dashboards, because of its
capabilities of advanced search.
POWER BI
Power BI software solution has been supported and developed for business analytics and
business intelligence, by Microsoft, power BI, at its core stands as online service, consisting
several options related to interaction, while several connection outlets to data are featured, by
software and services of third party.
The Power Bi tool is an interface based on the web with the features varying to limited data
sources controls from customizable visualizations. Available functionality can be expanded
by desktop applications, to a better extent, with some tools added to cleanse data and
normalization.
It’s mobile app is made available for various platforms. Sharing insights with it is simple
amazingly, through work publishing to service of Power BI and forming dashboards lively
from a reports combination that makes easy to follow up and centralized data communication,
for each of the participants.
Basically Power BI is designed to be powerful and robust, though it looks minimalistic and
concise and has its own pros and cons, like other tools.
Power BI architecture follows other major products of Microsoft. The best part is that the
interface is familiar for Windows users. A good part with Power BI is that it is integrated
tightly with SQL Server, Azure Cloud Service, MS Excel and other Microsoft tools.
Features
 Power BI tool is made available to basic users for free, allowing to explore initially.
 The tool has dashboards interactive with data fed in real time

 The tool supports several ways for data import and incorporation, like cloud services,
third party, excel spreadsheets and streaming data connections.
 It consists of simple API to integrate different applications with Power BI.
 Support multiplatform, like mobile desktop, web
 It allows various ways for dashboards and share reports
Usability
Power BI has the interface, very easy to use most common Windows users. The outlook of
many depictions and controls is similar to MS Excel and other products of MS Office and so
the user can gain profound understanding the environment and creating reports.
Pricing
The pricing policy of Microsoft for Power BI is highly democratic and accessible to many
users. It has simple pricing structure.
COGNOS ANALYTICS BY IBM
Cognos Analytics business intelligence tool is an integrated business intelligence suite, which
is web-based. The tool provides tools for monitoring of metrics and events, analytics,
reporting and scorecarding. Various information requirements can be met by various
components of the software. Cognos consists of basic components, called query studio, event
studio, congnos connections, report studio, workspace, analytics studio and workspace
advanced. There are also Windows-based components, like cube designer, framework
manager, map manager, transformer and lifecycle manager. Some more components it
includes are Go! Office, Go! Dashboard, Go! Search.
Functionalities
There are various functionalities available in Cogno, by IBM.
 Cognos connection stands as a web Cognos BI portal. It is the initial step to access
basic information and functionality of Cognos.
 Business Insight enables the user for interactive and sophisticated workspaces
building and using, through its content and external sources of data.
 Report Studio is a tool for report authoring used by many professional authors and
developers of report, for creating managed and sophisticated reports.
 Event Studio is a tool for notifications used for decision makers to alert in the events’
organizations as they occur, to make decisions effectively and timely.
 Query Studio is a tool for reporting to create simple reports based on simple queries.
 Transformer component is referred as multi-dimensional data modelling to use with
later releases.
 Analysis Studio for better understanding of the business and discover answers for the
questions, with respect to their business.
 Metric Studio tool stands as the metrics and scorecarding.

BIG DATA ARCHITECTURE SOLUTION
There are numerous tools and architectures that are technically suitable and feasible to
implement the telecom project. However, because of the great flexibility and most
importantly exclusive architectural support makes it stand apart from the competitors, like
Qlikview, Power BI and Congos. The architecture is easy to understand and implement with
intuitive user interface and most importantly, the data can be accessed from various sources
and integrated, before creating the report. And more significant aspect is that it can integrate
with other modern big data platforms. So, the telecom project has been decided to be
implemented with the Tableau architecture.
Telecom wants to make use of big data and create better analysis of the customers and their
respective choices, to perform the best business with them and improve their profits. Telecom
also wants to make use of Big Data to explore the following opportunities.
Monitoring and controlling the network traffic usage to improve the service
Identifying fraudulent activity using voice recognition and data record
Develop better customizing plan for customer
Business Strategy
The business goals can be achieved by the company, with the following strategy.
1. Predict the customer real and using analytics tools and deliver better customer
experiences and create new opportunity. It improves precise marketing and decreases
the customer turnover.
2. Monitor usage and message log of network and ensure quality distribution for and
predict the usage. It helps monitoring and controlling the network traffic usage for
better service.
Data about the customers and network can be collected from social media and other data
sources. Using the Tableau architecture realistic relation between sales and revenue is
examined and optimize marketing activities and budgets.
Architecture

Figure: Architecture for Telecom Business Strategy
Tableau architecture is chosen since it is n-tier client server and highly scalable architecture.
The telecom customers and so database keeps scaling up every year and the architecture must
support the increased database.
Data Server – Tableau data server is multi-threaded and so scales up. It can be scaled out
with multi-process enabled. Tableau server provides integrated clustering. It is enough
secured and supports higher availability. This server runs both on virtual and physical
machines.
Data Layer – Tableau supports any data architecture selected. It has no limitations for the
database, stored in any one system. Tableau is able to work with heterogeneous environment
and majority of the organizations possess this environment. Tableau is able to work with any
and all kinds of environments even simultaneously. It also allows simple alternatives for data
update to be well responsive and quick with the Data Engine, which is in quick in-memory.
Data Connectors – Various conenctors are includes in Tableau, for databases, for instance,
Oracle, SQL Server, Microsoft Excel, Vertica, Teradata, Cloud Hadoop and many more.
When no local connector is present, a non-specific ODBC connector, for any kind of
frameworks. This way, Tableau allows collaborating data in two modes, in-memory and live
connection. Hence, the user or client can switch in between these two modes and association,
as chosen.
Live Connection – Tableau’s data conenctors control the data infrastructure through
dynamic MDX or SQL statements transferring to the source database directly, instead data
import. The advantage of connecting the data to live is while optimized quick and analytics
database is used. Additionally, it also utilizes unlimited data and Tableau works as analytics
client as front end to many biggest databases.
In-Memory – In-memory Data Engine is optimized and made faster for analytics. So,
connecting data and extracting data can be done with just one click. So, its data engine allows
faster queries and extractS answers from millions of rows, by fully consuming the entire
system. It does not depend on the quantity of memory as the Data Engine consumes whole
disk storage, cache memory and RAM.
Components – These components enable various functionalities of the tool and extract the
results through Application server or other servers. In this case, two components are enabled
that handle the authentication and authorizations of use and VizQl converts the queries to
visualizations.
Gateway – Gateway stands as a secured communication between the servers and clients.
Client – Client finally accesses the extracted information through web, desktop or mobile.
The results are shown in the dashboard.

CONCLUSION
Every business organization makes use of business intelligence and data analytics and
extracts the information that can best be used to take the business decisions and enable new
business functionalities accordingly. There are several business intelligence tools available in
the industry and the best one, Tableau tool and its architecture is exploited to the best way to
implement the Telecom project strategy. There are numerous tools and architectures that are
technically suitable and feasible to implement the telecom project. However, because of the
great flexibility and most importantly exclusive architectural support makes it stand apart
from the competitors, like Qlikview, Power BI and Congos.
REFERENCES
Coker, Frank (2014). Pulse: Understanding the Vital Signs of Your Business. Ambient Light
Publishing. pp. 41–42
N.A. (2014). Company Overview of Tableau Software, Inc. Bloomberg.