Strategic Decision Making based on Real-Time Data Analytics€¦ · 68% of high-performers have real-time data integration capabilities. 52% of high-performers automate data capture

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Strategic Decision Making

based on Real-Time

Data Analytics

Version 2.1 May 2016


2

• Characteristics of a High-Performer

• Big Data Challenges

• Fast Data to Insight

• Analytics Solution / Service Offerings

Content


3 Characteristics of a High-Performer

High-performers obtain critical information within the decision window 80% of the time in which a decision window is the period of time when information is valuable for a choice at hand.

What makes a high-performer?

High-performers take 18 days on average to integrate a new data source into the business intelligence system.

68% of high-performers have real-time data integration capabilities.

52% of high-performers automate data capture process

High-performers take 114 days on average to complete a new business intelligence project.

The findings of high-performers leverage data capabilities based on a number of researches conducted by Aberdeen Group in 2014,


4 Big Data Challenges

Archives: Scanned documents, statements, forms, print stream files, etc.

More data from more sources than ever

Docs: XLS, PDF, CSV, DOC, PPT, HTML, XML, JSON, plain text file, email, etc.

Media: Videos, images, audio, streams, etc.

Data Storage: SQL databases, NoSQL, Hadoop, doc repository, file systems, etc.

Business Apps: CRM, ERP, CMS, SCM, HRM, web portals, etc.

Public Web: Government, weather, census, Wikipedia, etc.

Social Media: Facebook, LinkedIn, Twitter, Weibo, Blog, YouTube, Instagram, etc.

Machine Log Data: Event logs, server data, application logs, audit logs, CDRs, clickstream, etc.

Sensor Data: Mobile devices, smart meters, car sensors, medical devices, road cameras, etc.

Source: datafloq, November 2014



So many data sources, so little time

79%

78%

43%

31%

31%

19%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Internal structured data (e.g. customer, product, material data)

Transactional application data (e.g. ERP, CRM, SCM)

Internally-generated unstructured data

Externally-generated unstructured data

Internet-generated data (e.g. social media, customer sentiment)

Sensor / machine-to-machine data

Frequently Used Data Types

Source: Aberdeen Group, September 2014

n = 205



So many data sources, so little time

79%

78%

43%

31%

31%

19%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Internal structured data (e.g. customer, product, material data)

Transactional application data (e.g. ERP, CRM, SCM)

Internally-generated unstructured data

Externally-generated unstructured data

Internet-generated data (e.g. social media, customer sentiment)

Sensor / machine-to-machine data

Frequently Used Data Types

Source: Aberdeen Group, September 2014

n = 205

The Internet-of-Things will continue

to swell data volumes and increase

demand for faster data delivery


7 Fast Data to Insight

You must go faster!

Even the most profound and

detailed analysis of gigantic data

sets is meaningless if it occurs too

late and opportunities are gone.


67%

43%

33%

57%

Top performers

All others

Integration Approach

Real-time integration capabilities Batch-oriented integration only

8 Fast Data to Insights

Integration determines the speed

Source: Aberdeen Group, July 2014

n = 97


9 Analytics Solution / Service Offerings

A data-centric approach Adapting to your needs on a single platform

Low up-front

investment

Low Total Cost of

Ownership (TCO)

Industry

expertise Shorter time to

market

Proven infrastructure

and support

Single platform for

data integration

Data analytics

consulting services



Infinitum Analytics Solutions All our analytics solutions on Infinitum are built to help mid-market customers adopt business analytics solutions that are quick-start, feature-rich, production-ready, and cost-effective and do not require the complexity of procuring and maintaining either hardware of software licenses.

Traditional Data Sources Unstructured Text Data

Unstructured Video Data

Traditional Data Sources Unstructured Text Data

Unstructured Video Data Unstructured Audio Data

Sensor Data

Social Media Analytics

Enterprise Analytics Platform

Retail / Customer Analytics

Video Analytics People Counting

Video Analytics Crowd Management

Signage Audience Analytics

Personalized Recommendation Engine

Prescriptive Business Process Decision Making

Intelligent Inventory Management



Social Media Analytics Aka social listening or social media monitoring

Capture and analyze the social conversations of a brand, its services and its competitors on popular social media channels such as Facebook, YouTube, Weibo, discussion forums and news sites

Capture the true voice of their customers about sentiment towards the company’s brands, products, services and marketing campaigns; and purchase preferences and opinions

Value Proposition Increase Customer Satisfaction

Protect brand image by monitoring and taking actions to manage brand issues and PR crisis

Engage unhappy customers on social media and other offline channels Improve products and enhance customer touch points by analyzing customers’

opinions of products and services

Increase Revenue

Improve marketing campaign effectiveness by closing the feedback loop



Video Analytics Use cost-effective IP-cameras and machine learning algorithms to

detect objects and recognize faces, estimate gender, race, age group, emotion, stay duration, flow traffic, etc.

Able to complement and correlate other analytics solution for advanced analytics

Not for military use

Value Proposition Increase Revenue

Capture and study real customer behaviors in real-time Measure impressions for high-return product display or rent determination

Optimize Cost

Effectively allocate staff and resources based on real-time monitoring

Increase Customer Satisfaction

Improve customer services by knowing your customer



Retail / Customer Analytics Draw customer insight from machine learning algorithms on customer

profile and behavior data

Empower end-users to use interactive data visualization to analyze data in real-time for better decision making

Provide the right information to the right customer at the right time through the right channel

Value Proposition Increase Revenue

Boost marketing campaign effectiveness and conversion rate Unlock and estimate the customer lifetime value

Optimize Cost

Effective and efficient planning supported by data-based forecast

Increase Customer Satisfaction

Produce personalized marketing campaigns or target marketing



To be a high performer

1. Discard traditional data warehousing

notions and embrace automation to

streamline processes and free up IT

resources

2. Continuously improve and adopt

automation in order to bring down the

integration and implementation times

Documents

Strategic Decision Making based on Real-Time Data Analytics€¦ · 68% of high-performers have real-time data integration capabilities. 52% of high-performers automate data capture