Centralized HADOOP Secure Data Store with Data Integration ... · ITC Infotech’s Big Data Practice The goal of the Big Data practice in ITC Infotech is to provide consulting and
Post on 10-Mar-2020
6 Views
Preview:
Transcript
Centralized HADOOP Secure Data Store with Data Integration & BI Solution Enabled Efficient Data Processing & Enhanced Information Security
SITUATIONThe customer wanted to centralize existing disperse data sources and create a unified master data store. Multiple data sources being consumed manually using error-prone steps prevented the customer from obtaining true insights on demand in near real time. The customer also wanted to go beyond transactional data and combine it with social media information to facilitate sentiment analysis. Data sensitivity around PII and governance was further complicating the situation
IMPACTThe existing data warehousing systems were not able to handle huge data growth and were also unable to integrate unstructured data to extract business insights. Cost of licenses for storing and processing huge data with existing BI tools was comparatively high
RESOLUTIONITC Infotech helped the customer create a centralized Hadoop data store for different varieties of data (structured, unstructured and semi structured). Data security was achieved in the Hadoop environment using a security key provided by the customer
The CustomerThe customer is a mobile security provider headquartered in Sunnyvale, California, United States. The company serves more than 5,000 organizations worldwide in industries such as financial services, healthcare, manufacturing, energy and utilities, legal, government, and technology. The company makes products for managing and securing mobile devices in a business environment and focuses on securing apps and data on mobile devices. With revenue of 25 million USD, the customer has a strong operational base in many countries across the world.
The NeedThe customer wanted to empower internal business teams with the right kind of information at near real time and wanted to eliminate manual intervention of Business Intelligence analysis to help achieve the strategic business goal. There was a need for enhanced data security in the new solution for sensitive enterprise data both at rest as well as in motion. Considering the high license costs of traditional data warehousing and business intelligence tools the customer wanted to implement a cost-effective and scalable solution considering the future growth of data. Besides TCO, a critical requirement of the new BI solution was a capability for Analytical Cube Modeling, visualization features, Time to Value and vendor support. After identifying new tools, the customer also required a road map to migrate existing dashboards to the new system.
The SolutionITC Infotech evaluated some of the major Hadoop distributions such as Cloudera, Horton Works, MAPR and AWS EMR as they support most of the business requirements while containing TCO at the same time based on usage. The customer preferred AWS EMR as i t prov ides mul t ip le so lut ions towards Key management and we implemented AWS EMR in conjunction with S3 storage. The primary objective of this project was to deliver analytical dashboards to business users using the centralized BIGDATA store.
ITC INFOTECH adopted a detailed test strategy defining the overall approach and covering various aspects of testing relevant to the engagement. We further implemented test plans and test cases with Requirement Traceability Matrix and generated test completion reports along with results analysis. The following are some of the business cases targeted by the customer:
Tracking customer contract
Tracking existing contract type, license type, license cost and duration to provide actionable insights to the customer on how to cross-sell and upsell licenses
This would also enable them to promptly and effectively engage with customers
2014 2015 2016 2017
Ja
n
Fe
b
Ma
r
Ap
r
Ma
y
Ju
n
Ju
l
Au
g
Se
p
Oc
t
No
v
De
c
Ja
n
Fe
b
Ma
r
Ap
r
Ma
y
Ju
n
Ju
l
Au
g
Se
p
Oc
t
No
v
De
c
Ja
n
Fe
b
Ma
r
Ap
r
Ma
y
Ju
n
Ju
l
Au
g
Se
p
Oc
t
No
v
De
c
Ja
n
Fe
b
Ma
r
Ap
r
Ma
y
Ju
n
Ju
l
Au
g
Se
p
Oc
t
No
v
De
c
0M
5M
10M
Rr
Pe
r M
on
th
2,8
78
,81
8.5
9
3,0
97
,97
0.3
3
4,0
91
,69
8.8
7
2,4
54
,65
2.4
6
3,0
10
,76
8.0
6
3,5
64
,78
8.2
6
4,5
45
,86
4.6
0
1,8
52
,48
4.1
4
1,9
10
,90
4.0
4
2,2
60
,98
2.1
4
2,3
78
,66
1.9
4
3,8
62
,29
7.3
2
5,4
76
,93
5.9
5
5,5
55
,65
2.2
5
4,7
59
,97
6.5
9
4,6
26
,39
4.0
7
5,3
54
,18
2.5
7
5,8
22
,85
1.5
7
6,1
07
,86
3.7
7
6,0
48
,18
5.8
6
5,2
51
,11
3.8
6
4,7
06
,33
9.7
0
5,4
38
,18
3.1
4
5,5
87
,36
3.2
2
3,7
40
,29
5.5
5
2,9
44
,76
2.1
5
3,4
05
,54
1.6
8
4,6
38
,72
6.3
3
3,1
77
,57
4.2
6
3,1
51
,05
8.0
6
4,6
00
,43
7.4
0
2,5
22
,33
7.0
0
3,8
92
,97
4.2
2
3,0
34
,93
9.3
2
2,8
30
,42
4.8
2
4,0
70
,07
8.4
1
1,0
45
,42
9.2
8
2,3
27
,11
8.4
7
2,2
84
,96
2.6
3
1,2
43
,36
2.3
3
1,1
41,2
12
.73
2,0
69
,04
4.0
0
1,9
52
,93
6.3
4
1,4
35
,61
8.7
4
1,8
70
,38
8.9
2
1,5
26
,01
3.1
2
1,4
11
,94
7.1
1
841,7
44
.88
MRR Graph
Tracking application usage to understand existing distribution patterns
Based on device form factor (Smartphone or Tablet or Ipad)
Based on mobile platform (IOS or Android or Windows)
Verify if the current development aligns with the trend and accordingly come up with action plans to maximize revenue by focusing on the factor of highest growth and reducing cost of investment on diminishing platforms / systems
Creating a single view of the customer
Unifying transaction data from various sources with social media data to enable the customer to have a single view that will help them identify customer retention and renewal (churn), application segmentation, risk profile, etc.
Business Benefits Centralized data warehousing system integrated
with various source systems and subject areas
Business outbound dashboards and feeds to business users to assist in customer sentimental analysis and statistical analysis
Enhanced business decision making with increased visibility into the single status of all applications and products
Data security at rest and in motion and masking of customer’s Personal Identification Information (PII)
Enhanced data quality and data standardization
Increased accuracy and efficiency through solution automation
Near real-time/on demand report generation through automated data pipeline implementation
Performance improvement of end-to-end BI solution from days to minutes
Reduced license costs for infrastructure and tools
Ch
um
Pro
pe
nsity
Risk
Pro
file
Lia
bili
ty
Ne
ed
fo
r fu
nd
s
Product
PropensityWillingness to Pay
Segment
Custo
me
r
Life c
ycle
Customer Life
time value
Profit
ability
ChannelPreference
Assets
Products held
Cost
to serve
Re
ve
nu
e f
rom
cu
sto
me
r
Transaction
Demographics
CreditBureaudata
Financia
l
Prote
ction
Other Fls
data
Survey Data
Channel
data
(CC, w
eb)
Government agency
datard3 partypaymentdata
Customero360 view
Mobility Index Report
Quarterly AppGrowth Quarterly AppGrowthby Device Platform
Quarterly AppGrowthby Device Form Factor
App Distribution byIndustry
Apps Distribution byOrganization
To be Identied AppCategories/DeviceForm Factors
Industry
Business andProfessional
Education Energy andUtilities
Entertainmentand Media
FinancialServices
Healthcare HealthCare High Tech Hospitability Insurance Manufacturing Other Public Sector/Government
0K
200K
400K
Ap
p c
ou
nt
116,478
132,807
105,102
70,175 55,25944,387
67,683
53,314
71,162
47,352
App Distribution by Industry
Real Estate Retail Trade Transportationand Warehouse
Wholesale andRetail
IndustryAll
App Category
SECURE BROWSER
CUSTOM APP
SECURE IM
GOOD WORK
DOC EDITING
DOC ACCESS
MDM
NOTES
BIZ INT
EXAMPLE APP
VERTICAL
ITC Infotech’s Big Data Practice
The goal of the Big Data practice in ITC Infotech is to provide consulting and implementation services to enterprises and help them transform their data architecture to use modern data technologies. Using these technologies, enterprises are able to use greater variety, larger volume and higher velocity of unstructured and structured data together to generate deeper business insights. The benefits of big data technologies include not better insights, but a lower cost and more scalable, future ready data infrastructure.
ITC Infotech’s Big Data practice has developed deep implementation capabilities; end-to-end management consulting and system integration expertise, coupled with a robust global delivery model and standard quality management processes.
For more information, please write to:contact.us@itcinfotech.com
© 2016, ITC Infotech. All rights reserved.
www.itcinfotech.com
top related