The Total Economic Impact™ Of Teradata Aster Discovery ...

A Forrester Total Economic

Impact™ Study

Commissioned By

Teradata

Project Director:

Anish Shah

October 2014

The Total Economic

Impact™ Of Teradata

Aster Discovery Platform Cost Savings And Business Benefits Enabled By Implementing Teradata’s Aster Discovery Platform

Table Of Contents

Executive Summary .................................................................................... 1

Disclosures .................................................................................................. 2

TEI Framework And Methodology ............................................................ 3

Analysis ........................................................................................................ 4

Financial Summary ................................................................................... 12

Appendix A: Interviewed Organization Description ............................. 15

Appendix B: Total Economic Impact™ Overview ................................. 16

Appendix C: Glossary ............................................................................... 17

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1

Executive Summary

Teradata commissioned Forrester Consulting to conduct a

Total Economic Impact™ (TEI) study and examine the

potential return on investment (ROI) enterprises may

realize by implementing Teradata Aster Discovery

Platform. The purpose of this study is to provide readers

with a framework to evaluate the potential financial impact

of the Aster Discovery Platform on their organizations.

To better understand the benefits, costs, and risks

associated with an Aster Discovery Platform

implementation, Forrester conducted an in-depth

interview with a long-term customer using Teradata’s

Aster Discovery Platform. This customer had over five

years of experience using the Aster Discovery Platform to

help implement a big data analytics and discovery

solution. The platform enabled the organization to

streamline fragmented data, reduce costs of hiring

technical resources, increase the time to business

insights, integrate with its other systems, and align with its

cloud strategy.

Prior to implementing the Aster Discovery Platform, the

customer was using a third-party website for all its

reporting, analytics, and operational needs. The

organization was collecting significant clickstream logs about interactions on its website. However, it did not have the

capability to process it and derive insights to make its business model more efficient. It also was quickly finding out that

writing MapReduce code for every business query was not really going to provide the scalability it required. With a limited IT

support staff to meet the demands of the business, the organization started looking for a platform to provide it with big data

analytics and discovery capabilities to analyze compiled customer data. In looking for the right vendor, the company chose

the Aster Discovery Platform for the following reasons:

• It has the ability to data model, warehouse, and work with unstructured data.

• It can reduce labor costs through more readily available skill sets that can manage the platform.

• It has visual tools to help drive key business insights and improve marketing efficiency.

ASTER DISCOVERY PLATFORM GENERATES SALES, PRODUCTIVITY, AND MARKETING EFFICIENCY INCREASES

Our interview with a large online retailer and subsequent financial analysis found that the organization experienced the risk-

adjusted ROI, benefits, and costs shown in Figure 1. (See Appendix A for a description of the organization.)Figure 1

Financial Summary Showing Three-Year Risk-Adjusted Results

ROI: 106%

Total 3 Year NPV: $3.1 million

Payback: 13.9 months

Total 3 Year benefits: $6.1 million

Source: Forrester Research, Inc.

Teradata Aster Discovery Platform is a big data

analytics and discovery solution that allows

companies to derive high-impact insights from big

data through an integrated solution. The interviewed

organization benefited from an increase in prospect

conversion, an increase in both IT and end-user

productivity, and an increase in marketing efficiency.

The Total Economic Impact study highlighted the

following costs and benefits for the interviewed

organization:

Three-year total benefits: $6.1 million.

Hardware and software license costs: $1 million

initial and $200,000 per year ongoing.

Annual data engineer, IT, and business analyst

support costs of $495,000 in Year 1 and

$765,000 ongoing.

Three-year NPV: $3.1 million.

2

› Benefits. The interviewed organization experienced the following risk-adjusted benefits:

• Increase in prospect conversion resulting in direct impact to bottom line profits. The interviewed organization

can directly attribute an increase in prospect conversion and an increase in net profit margin from the insights that

are generated from its investment in the Aster Discovery Platform. For the interviewed organization, the percentage

lift on its net profit margin happens gradually with a 1% lift in Year 1 and going up to a 3% lift by Year 3.

• Increase in IT and end user productivity. The interviewed organization estimated 20% of its total employees (IT

and business) have a direct benefit resulting from the implementation of the Aster Discovery Platform. These 20% of

employees see a gradual increase in their productivity from Year 1 to Year 3 due to how quickly insights can be

generated and the business optimized.

• Increase in marketing efficiency. The interviewed organization has been able to positively influence its use of its

marketing dollars due to the analysis and insights generated through the implementation of the Aster Discovery

Platform in its environment.

› Costs. The interviewed organization experienced the following risk-adjusted costs:

• Hardware and software costs include initial implementation cost of $1 million and ongoing costs of

$200,000 per year. These are the initial one-time fees paid to Teradata for purchasing the hardware and software to

host the Aster Discovery Platform in its environment as well as the ongoing cost of maintaining and supporting the

Aster Discovery Platform that has been incurred by the interviewed organization.

• Full-time equivalent (FTE) costs to support the Aster Discovery Platform are $465,000 in Year 1 and

$765,000 per year after Year 1. Once the interviewed organization implemented the Aster Discovery Platform, it

had to hire one full-time data scientist, two full-time technology resources, and two full-time business analysts

beginning in Year 2 to achieve its benefits from its investment.

Disclosures

The reader should be aware of the following:

› The study is commissioned by Teradata and delivered by Forrester Consulting. It is not meant to be used as a competitive

analysis.

› Forrester makes no assumptions as to the potential ROI that other organizations will receive. Forrester strongly advises

that readers use their own estimates within the framework provided in the report to determine the appropriateness of an

investment in Teradata Aster Discovery Platform.

› Teradata reviewed and provided feedback to Forrester, but Forrester maintains editorial control over the study and its

findings and does not accept changes to the study that contradict Forrester’s findings or obscure the meaning of the study.

› Teradata provided the customer name for the interview but did not participate in the interview.

3

TEI Framework And Methodology

INTRODUCTION

From the information provided in the interview, Forrester has constructed a Total Economic Impact (TEI) framework for those

organizations considering implementing Teradata Aster Discovery Platform. The objective of the framework is to identify the

cost, benefit, flexibility, and risk factors that affect the investment decision.

APPROACH AND METHODOLOGY

Forrester took a multistep approach to evaluate the impact that Teradata Aster Discovery Platform can have on an

organization (see Figure 2). Specifically, we:

› Interviewed Teradata marketing, sales, and IT personnel, along with Forrester analysts, to gather data relative to the Aster

Discovery Platform and the marketplace for Aster Discovery Platform.

› Interviewed one organization currently using Teradata’s Aster Discovery Platform to obtain data with respect to costs,

benefits, and risks.

› Constructed a financial model representative of the interview using the TEI methodology. The financial model is populated

with the cost and benefit data obtained from the interview.

› Risk-adjusted the financial model based on issues and concerns the interviewed organization highlighted in interview. Risk

adjustment is a key part of the TEI methodology. While interviewed organizations provided cost and benefit estimates,

some categories included a broad range of responses or had a number of outside forces that might have affected the

results. For that reason, some cost and benefit totals have been risk-adjusted and are detailed in each relevant section.

Forrester employed four fundamental elements of TEI in modeling Teradata Aster Discovery Platform’s service: benefits,

costs, flexibility, and risks.

Given the increasing sophistication that enterprises have regarding ROI analyses related to IT investments, Forrester’s TEI

methodology serves to provide a complete picture of the total economic impact of purchase decisions. Please see Appendix

B for additional information on the TEI methodology.

FIGURE 2

TEI Approach


Perform due diligence

Conduct customer interview

Profile customer

organization

Construct financial

model using TEI framework

Write case study

4

Analysis

INTERVIEWED ORGANIZATION

For this study, Forrester conducted an in-depth interview with the director of data engineering whose organization

implemented Teradata’s Aster Discovery Platform. The interviewed organization has the following profile:

› It is a privately held organization with over 1,000 employees.

› It is an online eCommerce retailer for high-end branded merchandise with over $600 million in annual revenue.

› It is headquartered in the Northeast United States with employees across multiple countries. Eighty-five percent of the

employees are based in the United States, and many of them work remotely.

› Some countries have their own country-specific website that is treated as a separate entity. The director of data

engineering is responsible for managing all the different eCommerce platforms.

› Information technology resources for the organization are split between the United States and Ireland.

Based on this interview, Forrester constructed a TEI framework and an associated ROI analysis that illustrates the areas the

organization identified as having the greatest financial impact and developed a model of costs and benefits.

INTERVIEW HIGHLIGHTS

Situation

In 2009, the interviewed organization was using a third-party website

platform to support its analytics needs. The company was collecting

clickstream logs about customer behavior and website interaction,

and it had no meaningful way to process and act on the data it was

collecting. With the third-party website, the organization started using

Elastic MapReduce to understand its data, and it quickly found out

that writing MapReduce code for every single question that the

business needed to answer was not going to provide the scalability

that it needed. This is when the organization started looking for a

platform to provide big data analytics and discovery capabilities and

allow it to more efficiently analyze all the data it was collecting. The

interviewed organization had discussions and sent out request for

proposals (RFPs) to assess the right data warehouse platform for

them.

Solution

After evaluating multiple vendors, the interviewed organization selected Teradata’s Aster Discovery Platform for its flexibility

and its strength in housing and analyzing both structured and unstructured data. Furthermore, the decision to go with Aster

Discovery Platform was because of its ability to interact with many other systems in the organization’s environment. The

organization wanted a platform to work in conjunction with Cognos, Tibco Spotfire, and complement Apache Hadoop.

The interview revealed that:

› It took the organization between two years before experiencing the full benefits of Aster Discovery Platform. It

took the organization two years to fully achieve all three of the quantifiable benefits linked to its Aster Discovery Platform

“We have a lot of test cases

and product changes that we

have been able to make

internally as a result of the

analytics that is taking place

on the platform.”

~Director of data engineering, online retailer

5

investment (increase in prospect conversion, increase in employee productivity, and increase in marketing efficiency). Both

employees and processes needed to adapt to the learnings and the insights that could be generated through this platform.

› The organization wanted to invest in a platform that would complement Apache Hadoop. It was important for the

interviewed organization to choose a big data analytics and discovery platform that complemented Apache Hadoop, which

was already used in its environment. For example, the interviewee said, “If I need to answer a very small question quickly,

that is not going to happen on Hadoop. If I need to answer a very large question on unstructured data, we may need to use

Hadoop.” The interviewed organization also mentioned that if it wants to store a lot of data that it will be infrequently

accessing, then economically Hadoop makes more sense than the Aster Discovery Platform.

› The organization’s performance improved dramatically after implementing the Aster Discovery Platform. The Aster

Discovery Platform performed a lot better than Elastic

MapReduce, which the organization was using before. In the

Elastic MapReduce world, the data engineering team would have

to write a Java program that could answer a query, deploy the

Java group program, and then run Elastic MapReduce to mine

the data set and get answers out. With the Aster Discovery

Platform, the organization could just type in a SQL query.

› The interviewed organization’s planning process has

become much better. With the Aster Discovery Platform, the

organization’s planning process has become more efficient. The

director of data engineering expressed, “If we can predict what

products are going to arrive late then that can help us more

efficiently plan our sale calendar and more efficiently plan our

shops.” Being able to better forecast and predict through

predictive insights allowed the organization to become more

efficient within the product life cycle.

› The organization found it easier to find the skill set to

generate insights through the Aster Discovery Platform. The

interviewed organization claimed that because of the platform’s

ready-to-use big data functionality, acquiring data, performing

analysis, and presenting output can be done by a wide variety of

IT skills sets and resources. The organization does not need a full team of expensive data scientists and engineers to

manipulate and use data.

BENEFITS

The interviewed organization experienced a number of quantified benefits in this case study:

› Additional net profit from increasing prospect conversation rate.

› Increased savings from IT and end user productivity.

› Lift in sales from increased marketing efficiency.

Another important benefit mentioned by the interviewed organization was the ease of deploying the system into its

environment. While implementation time depends on a number of factors, the organization regarded the ease of working with

Teradata’s implementation team to install the Aster Discovery Platform into its environment and realize an accelerated

payback for its investment.

“For us, it has been relatively

easy to monetize and justify

our investment in Aster

Discovery Platform; the

changes that have resulted

from the product have offered

us much increase in revenue.”

~Director of data engineering, online retailer

6

Additional Net Profit From Increasing Prospect Conversion Rate

The interviewed organization noted that the use of Teradata’s Aster Discovery Platform allowed it to better analyze and

process large volumes of website engagement data. The organization could then apply this analysis to make adjustments to

its sales process, ultimately leading to an increase in the prospect conversion rate. The director of data engineering said:

“Within three years our business was able to enhance our acquisition process and customer experience through the insights

delivered by the Aster Discovery Platform [so] that we could see material impact to our bottom line.” The Aster Discovery

Platform allows business users to gain access to customized reports and dashboards and develop ad hoc queries to deliver

real-time intelligence to enhance their customer experience. The ability to handle thousands of queries through a simplified

system management process allows the interviewed organization to provide a more targeted customer experience that

directly leads to sales.

The interviewed organization had approximately $600 million in revenue in Year 1, with an average net profit margin of 8% or

$48 million. Upon implementing the Aster Discovery Platform, the interviewed organization could attribute a lift in 1% in net

profit in Year 1, which resulted in a total three-year risk adjusted benefit amount of over $2.9 million (see Table 1). The

interviewed organization conducted extensive tests to understand how many additional prospects converted once new data-

driven insights on prospect behavior were implemented. The interviewed organization also expressed that there was a

learning curve for it to understand and operationalize the insights from the Aster Discovery Platform. The director of data

engineering stated, “It took us about three years to realize the full benefits and come to a steady state from our purchase of

this big data analytics and discovery platform.”

TABLE 1

Additional Net Profit From Increasing Prospect Conversion Rate


Increased Savings From IT And End User Productivity

For the interviewed organization, the Aster Discovery Platform became the central place where data is aggregated and is the

source of information the business uses to make decisions on a daily basis within the organization. Noted benefits included

ease of data aggregation, reduced time of writing queries, interaction with other internal systems, and web-based reporting

that allows the business to gain access to real-time actionable insights. The director of data engineering stated: “My data

scientists and DBAs now are much more efficient, and my end users have quicker access to information and reporting that

they can access themselves using the Aster Discovery Platform’s simplified web interface.”

Ref. Calculation Initial Year 1 Year 2 Year 3 Total

Present

Value

A1 $600,000,000 $630,000,000 $661,500,000

A2 8% 8% 8%

A3 A1*A2 $0 $48,000,000 $50,400,000 $52,920,000

A4 1% 2% 3%

95%

Atr $0 $456,000 $957,600 $1,508,220 $2,921,820 $2,339,098

Net profit margin

Metric

Gross revenue estimates

Additional profit impact

from customer conversion

Percent lift directly attributed to

better customer experience

from Aster Discovery Platform

Net profit

Risk adjustment

7

The interviewed organization has 1,000 employees, of which 20% directly rely on the Aster Discover Platform for their daily

activities. During the first year, the interviewed organization estimated about a 1% lift in both IT and end user employee

productivity, which increased to 4% by Year 3. At an average fully burdened cost per FTE of $175,000, the interviewed

organization realized a three-year risk-adjusted net benefit of over $2.3 million (see Table 2).

TABLE 2

Increased Savings From IT And End User Productivity


Lift In Sales From Increased Marketing Efficiency

Prior to implementing the Aster Discovery Platform, the interviewed organization was having a hard time navigating through

large volumes of data to identify and engage with its customers. There was an increased amount of pressure to enhance the

return on the approximate 15% of top-line revenue that the interviewed organization was allocating for its annual marketing

budget. A key objective of the IT organization was to assist in analyzing its data and optimize its go-to-market approach to

identify and retain customers. After its implementation of the Aster Discovery Platform, the interviewed organization saw

efficiencies across its marketing efforts. It was able to optimize targeted marketing campaigns, improve its communication

strategy, optimize its website and product mix, and influence its pricing strategy, as well as target customers with a relevant

and well-timed offer strategy.

The interviewed organization spends about 15% of its top-line revenue on marketing to win and retain its customers. After its

implementation of the Aster Discovery Platform, the interviewed organization claimed that the direct efficiency gain was 0.5%

in Year 1, which increased to a 1% efficiency gain in years 2 and 3 (see Table 3).


Present

Value

B1 1,000 1,000 1,000

B2 20% 20% 20%

B3 $175,000 $175,000 $175,000

B4 1% 2% 4%

Bt B1*B2*B3*B4 $0 $350,000 $700,000 $1,400,000

95%

Btr $0 $332,500 $665,000 $1,330,000 $2,327,500 $1,851,108

Metric

Number of employees

Increase in employee

productivity directly due to

Aster Discovery Platform

Risk adjustment

Increase in employee

productivity directly due to


Percent of employees whose

productivity increases directly

from insights gained from Aster

Discovery Platform

Average burden rate of

employee

Percent increase in productivity

8

TABLE 3

Lift In Sales From Marketing Efficiencies


Total Benefits

Table 4 shows the total of all benefits across the three areas listed above, as well as present values (PVs) discounted at

10%. Over three years, the interviewed organization expects risk-adjusted total benefits to be a PV of approximately $6.1

million.

TABLE 4

Total Benefit Cash Flows (Risk-Adjusted Estimates)



Present

Value

C1 $600,000,000 $630,000,000 $661,500,000

C2 15% 15% 15%

C3 0.5% 1% 1%

Ct C1*C2*C3*C4 $0 $450,000 $945,000 $992,250

100%

Ctr $0 $450,000 $945,000 $992,250 $2,387,250 $1,935,575

Risk adjustment

Increase in efficiency of

marketing directly

attributed to Aster Discovery

Marketing budget percent of

gross revenue


marketing directly attributed to


Metric

Gross revenue estimates


marketing directly attributed to


Ref. Initial Year 1 Year 2 Year 3 Total

Present

Value

Atr $0 $456,000 $957,600 $1,508,220 $2,921,820 $2,339,098

Btr $0 $332,500 $665,000 $1,330,000 $2,327,500 $1,851,108

Ctr $0 $450,000 $945,000 $992,250 $2,387,250 $1,935,575

$0 $1,238,500 $2,567,600 $3,830,470 $7,636,570 $6,125,781

Benefit Category

Increased prospect conversion rate through better

customer experience results in increase in profit

Total benefits (risk-adjusted)

Increase in employee productivity due to Aster

Discovery Platform leads to fewer FTE

requirements

Increase marketing efficiency

9

COSTS

The interviewed organization experienced two primary investment costs associated with the Aster Discovery Platform

solution:

› Initial hardware, software, and integration costs.

› Internal data scientist and support costs.

These represent the mix of internal and external costs experienced by the organization for initial planning, implementation,

and ongoing software maintenance associated with the solution.

Initial Hardware, Software, And Integration Costs

The initial hardware and software purchase price and implementation cost for the Aster Discovery Platform is $1 million,

which is reflective of the market rate for organizations with a similar profile to our interviewed organization. While the

interviewed organization leases its hardware for the Aster Discovery Platform, Forrester chose a costing model that is more

reflective of the majority of Teradata customers. This price is for a clustered system with multiple nodes. The nodes store the

distributed data and also work in parallel for all processing and analytic computations. The interviewed organization is

charged a $200,000 yearly maintenance fee from Teradata to manage and support its Aster Discovery Platform (see Table

5).

TABLE 5

Initial Hardware, Software, And Integration Costs


Internal Data Scientist And Support Costs

The largest cost category for the interviewed organization was the internal effort and resources to ensure the success of

supporting the Aster Discovery Platform. The interviewed organization hired a full-time data scientist with a fully burdened

cost of $250,000 per year once it implemented Teradata’s Aster Discovery Platform. The data scientist is highly proficient in

SQL and is responsible for developing and executing statistical and mathematical modeling to assist the business in its data

mining efforts. The interviewed organization also hired two additional Aster Discovery Platform IT support staff at a fully

burdened cost of $150,000 per year. The goal of the IT support staff is to manage both the Aster Discovery Platform

hardware and software, including performing maintenance and enhancing the interface based on business requirements.

In addition to technical support, the interviewed organization hired two business analysts starting in Year 2 to assist in

working with the business to really get the value of its investment in the Aster Discovery Platform. The business analysts


Present

value

D1 $1,000,000 $0 $0 $0

Dt $0 $0 $200,000 $200,000

100%

Dtr $1,000,000 $0 $200,000 $200,000 $1,400,000 $1,315,552

Metric

Aster Discovery Platform —

hardware purchase

Yearly ongoing hardware

maintenance

Risk adjustment

Yearly ongoing hardware

maintenance (risk-adjusted)

10

were hired to provide a bridge between business users and technical teams to ensure the technical solution meets business

needs. The total three-year cost for the interviewed organization is approximately $2 million (see Table 6).

TABLE 6

Internal Data Scientist And Support Costs


Total Costs

Table 7 shows the total of all costs as well as associated present values, discounted at 10%. Over three years, the

interviewed organization expects total costs to total a net present value of a little less than $3 million.

TABLE 7

Total Costs (Risk-Adjusted)


Present

Value

E1 250,000$ 250,000$ 250,000$

E2 300,000$ 300,000$ 300,000$

E3 0 300,000 300,000

Et $0 $550,000 $850,000 $850,000

90%

Etr $0 $495,000 $765,000 $765,000 $2,025,000 $1,656,987

Metric

Fully burdened data scientist

Total Aster Discovery Platform

support costs

Risk adjustment

Total Aster Discovery Platform

support costs (risk-adjusted)

Two fully burdened Aster support

staff ($150,000 per FTE)

Two analysts starting in Year 2

($150,000 per FTE)


Present

Value

Dtr ($1,000,000) $0 ($200,000) ($200,000) ($1,400,000) ($1,315,552)

Etr $0 ($495,000) ($765,000) ($765,000) ($2,025,000) ($1,656,987)

($1,000,000) ($495,000) ($965,000) ($965,000) ($3,425,000) ($2,972,539)

Cost Category

Aster Discovery Platform —

hardware and software license

costs

Internal data engineers and

support costs

Total costs (risk-adjusted)

11

FLEXIBILITY

Flexibility, as defined by TEI, represents an investment in additional capacity or capability that could be turned into business

benefit for some future additional investment. This provides an organization with the “right” or the ability to engage in future

initiatives but not the obligation to do so.

The Aster Discovery Platform is unique because it combines system designs along with built-in expertise and integrates

them into complete, optimized data analytics solutions for organizations. This fully integrated platform is not limited by

system memory and is scalable and can process large-scale queries across different business applications, including

customer churn, product affinity, fraud detection, and supply chain optimization.

The Aster Discovery Platform allows organizations to accelerate the speed at which organizations can access and gain

insights from their data while providing a simplified interface that can be used by many parts of an organization.

RISKS

Forrester defines two types of risk associated with this analysis: “implementation risk” and “impact risk.” Implementation risk

is the risk that a proposed investment in the Aster Discovery Platform may deviate from the original or expected

requirements, resulting in higher costs than anticipated. Impact risk refers to the risk that the business or technology needs

of the organization may not be met by the investment in the Aster Discovery Platform, resulting in lower overall total benefits.

The greater the uncertainty, the wider the potential range of outcomes for cost and benefit estimates. Table 8 shows the

variability in the benefit outcomes that customers similar to the interviewed organization may achieve from implementing

Teradata’s Aster Discovery Platform.

TABLE 8

Benefit And Cost Risk Adjustments

Benefits Adjustment

Additional net profit from increasing prospect conversation rate 5%

Increased savings from IT and end user productivity 5%

Costs Adjustment

Internal data scientist and support costs 10%


12

Financial Summary

The financial results calculated in the Benefits and Costs sections can be used to determine the ROI, NPV, and payback

period for the organization’s investment in the Aster Discovery Platform.

Tables 9 and 10 show the risk-adjusted ROI, NPV, and payback period values. These values are determined by applying the

risk-adjustment values from Table 8 in the Risks section to the unadjusted results in each relevant Cost and Benefit section.

TABLE 9

Cash Flow Chart (Risk-Adjusted)


TABLE 10

Cash Flow (Risk-Adjusted)


($2,000,000)

($1,000,000)

$0

$1,000,000

$2,000,000

$3,000,000

$4,000,000

$5,000,000

Initial Year 1 Year 2 Year 3

Ca

sh

Flo

ws

Financial Analysis (risk-adjusted)

Total Costs Total Benefits Cumulative Total

Initial Year 1 Year 2 Year 3 Total

Present

value

Total costs ($1,000,000) ($495,000) ($965,000) ($965,000) ($3,425,000) ($2,972,539)

$0 $1,238,500 $2,567,600 $3,830,470 $7,636,570 $6,125,781

($1,000,000) $743,500 $1,602,600 $2,865,470 $4,211,570 $3,153,242

106%

13.9

ROI

Payback period (months)

Summary

Total benefits

Total

13

Teradata Aster Discovery Platform: Overview

NEXT-GENERATION ANALYTICS ON ALL DATA INTEGRATED WITH SQL

The Teradata Aster Discovery Platform is the industry’s first next-generation, integrated discovery platform that provides

powerful, high-impact insights from big data through an integrated solution optimized for multiple analytics on all data with

speed and minimal effort. Using the Aster Discovery Platform, organizations attain unmatched competitive advantage and

drive pervasive adoption of big data analytics by every user based on their skills and preferences.

NEXT-GENERATION ANALYTICS FOR NEW INSIGHTS

The Teradata Aster Discovery Platform features SQL, SQL-MapReduce, SQL-GR graph analytic engine, and the open

source R engine that makes it easy to perform powerful and complex analyses across big data sets. Using these next-

generation engines, organizations can easily solve complex business problems such as path or pattern analysis, statistical

analysis, text analysis, social network and influencer analysis, fraud detection, supply chain management, network analysis,

and threat detection. The analytic engines integrate tightly together and can be invoked through a single SQL interface,

empowering analysts and data scientists to discover high-impact insights and reduce the complexity of big data analytics.

QUICKLY INGEST MULTISTRUCTURED DATA FOR ANALYTICS

The Teradata Aster Discovery Platform comes with new storage architecture that is optimized for discovery on all data,

leading to novel insights with the least amount of IT effort. The platform comes with Teradata Aster File Store, which enables

quick and easy ingestion of multistructured data (such as weblogs, sensor data, machine log data, etc.) for analysis without

any loss of fidelity or upfront schema definition effort. Applications that are built for HDFS can easily be run on data stored in

Aster File Store since it is fully compatible.

In addition to Aster File Store, the Aster Discovery Platform provides row and column store for storing relational data.

TERADATA ASTER SNAP FRAMEWORK FOR DISCOVERY

The Teradata Aster Discovery Platform features the unique Teradata Aster Seamless Network Analytics Processing (SNAP)

Framework for discovery that is designed to be standards-based and extensible and seamlessly integrates with existing IT

14

infrastructures. Teradata’s revolutionary SNAP Framework enables users to snap together multiple analytic engines and file

stores with ease, providing them with unmatched power and speed to delve deeply into data.

The SNAP Framework includes the following:

• Using the unified SQL interface, analysts and data scientists can invoke and combine various types of analytics

(such as graph, path/pattern, text, SQL, and statistical predictive analysis) in a single SQL statement.

• Integrated Optimizer takes the query with multiple analytics and parses it into multiple subqueries to be executed by

workload-specific execution engines like SQL-GR and SQL-MapReduce. The Integrated Optimizer features powerful

advanced optimizations like global collaborative planning and adaptive optimization that result in order of magnitude

gains in performance, such as eliminating redundant operations. Integrated Executor orchestrates the execution of

query and iterative phases across the multiple engines. It passes parameters and results across engines and

performs common workload management and monitoring across engines.

• Common Storage System and Services provide a unified data storage architecture that eliminates wasteful and

redundant effort. It is a plug-and-play system designed for typed data stores and provides common services such as

fault tolerance, replication, and security across the data stores.

DRIVE PERVASIVE ADOPTION OF BIG DATA

Insightful, interactive visualizations and an extensive portfolio of prebuilt functions applied from a familiar SQL interface

enable all users to participate in the discovery of insights using existing skills. The Teradata Aster Discovery Platform

features the Teradata Aster Discovery Portfolio, which provides a suite of ready-to-use functions that lead to high-value

insights for a wide variety of business use cases such as social network or influencer analysis, customer churn, behavioral

analysis, path to purchase, fraud, financial analysis, and personalized recommendations.

Teradata Aster Discovery Portfolio provides modules of functions for each of four steps in the discovery process: data

acquisition module, data preparation module, analytics module, and visualization module.

Teradata Aster Discovery Platform provides Teradata Aster Lens, which is an interactive web application for business users

and analysts to explore the results of analysis through interactive visualizations in a web browser. Teradata Aster Discovery

Platform integrates with several leading business intelligence and reporting tools, such as Tableau, MicroStrategy, Tibco

Spotfire, IBM Cognos, and SAP BusinessObjects.

15

Appendix A: Interviewed Organization Description

For this TEI study, Forrester has interviewed an organization that has implemented the Aster Discovery Platform to illustrate

the quantifiable benefits and costs of implementing Teradata’s Aster Discovery Platform.

The interviewed organization has the following characteristics:

› It is a privately held organization with over 1,000 employees.

› It is an online eCommerce retailer for high-end branded merchandise with over $600 million in annual revenue.

› It is headquartered in the Northeast United States with employees across multiple countries. Eighty-five percent of the

employees are based in the United States, and many of them work remotely.

› The organization spends approximately 15% of its top-line revenue in marketing-related activities.

› Some countries have their own country-specific website that is treated as a separate entity. The director of data

engineering is responsible managing all the different eCommerce platforms.

› Information technology resources for the organization are split between the United States and Ireland.

FRAMEWORK ASSUMPTIONS

Table 11 provides the model assumptions that Forrester used in this analysis.

The discount rate used in the PV and NPV calculations is 10%, and the time horizon used for the financial modeling is three

years. Organizations typically use discount rates between 8% and 16% based on their current environment. Readers are

urged to consult with their respective company’s finance department to determine the most appropriate discount rate to use

within their own organizations.

TABLE 11

Model Assumptions

Ref. Metric Calculation Value

C1 Cost per fully burdened data scientist $250,000

C2 Cost per fully burdened IT support staff $150,000

C3 Cost per fully burdened business analyst staff $150,000


16

Appendix B: Total Economic Impact™ Overview

Total Economic Impact is a methodology developed by Forrester Research that enhances a company’s technology decision-

making processes and assists vendors in communicating the value proposition of their products and services to clients. The

TEI methodology helps companies demonstrate, justify, and realize the tangible value of IT initiatives to both senior

management and other key business stakeholders.

The TEI methodology consists of four components to evaluate investment value: benefits, costs, flexibility, and risks.

BENEFITS

Benefits represent the value delivered to the user organization — IT and/or business units — by the proposed product or

project. Often, product or project justification exercises focus just on IT cost and cost reduction, leaving little room to analyze

the effect of the technology on the entire organization. The TEI methodology and the resulting financial model place equal

weight on the measure of benefits and the measure of costs, allowing for a full examination of the effect of the technology on

the entire organization. Calculation of benefit estimates involves a clear dialogue with the user organization to understand

the specific value that is created. In addition, Forrester also requires that there be a clear line of accountability established

between the measurement and justification of benefit estimates after the project has been completed. This ensures that

benefit estimates tie back directly to the bottom line.

COSTS

Costs represent the investment necessary to capture the value, or benefits, of the proposed project. IT or the business units

may incur costs in the form of fully burdened labor, subcontractors, or materials. Costs consider all the investments and

expenses necessary to deliver the proposed value. In addition, the cost category within TEI captures any incremental costs

over the existing environment for ongoing costs associated with the solution. All costs must be tied to the benefits that are

created.

FLEXIBILITY

Within the TEI methodology, direct benefits represent one part of the investment value. While direct benefits can typically be

the primary way to justify a project, Forrester believes that organizations should be able to measure the strategic value of an

investment. Flexibility represents the value that can be obtained for some future additional investment building on top of the

initial investment already made. For instance, an investment in an enterprise wide upgrade of an office productivity suite can

potentially increase standardization (to increase efficiency) and reduce licensing costs. However, an embedded collaboration

feature may translate to greater worker productivity if activated. The collaboration can only be used with additional

investment in training at some future point. However, having the ability to capture that benefit has a PV that can be

estimated. The flexibility component of TEI captures that value.

RISKS

Risks measure the uncertainty of benefit and cost estimates contained within the investment. Uncertainty is measured in two

ways: 1) the likelihood that the cost and benefit estimates will meet the original projections and 2) the likelihood that the

estimates will be measured and tracked over time. TEI applies a probability density function known as “triangular distribution”

to the values entered. At a minimum, three values are calculated to estimate the underlying range around each cost and

benefit.

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Appendix C: Glossary

Discount rate: The interest rate used in cash flow analysis to take into account the time value of money. Companies set

their own discount rate based on their business and investment environment. Forrester assumes a yearly discount rate of

10% for this analysis. Organizations typically use discount rates between 8% and 16% based on their current environment.

Readers are urged to consult their respective organizations to determine the most appropriate discount rate to use in their

own environment.

Net present value (NPV): The present or current value of (discounted) future net cash flows given an interest rate (the

discount rate). A positive project NPV normally indicates that the investment should be made, unless other projects have

higher NPVs.

Present value (PV): The present or current value of (discounted) cost and benefit estimates given at an interest rate (the

discount rate). The PV of costs and benefits feed into the total NPV of cash flows.

Payback period: The breakeven point for an investment. This is the point in time at which net benefits (benefits minus costs)

equal initial investment or cost.

Return on investment (ROI): A measure of a project’s expected return in percentage terms. ROI is calculated by dividing

net benefits (benefits minus costs) by costs.

A NOTE ON CASH FLOW TABLES

The following is a note on the cash flow tables used in this study (see the example table below). The initial investment

column contains costs incurred at “time 0” or at the beginning of Year 1. Those costs are not discounted. All other cash flows

in years 1 through 3 are discounted using the discount rate (shown in the Framework Assumptions section) at the end of the

year. PV calculations are calculated for each total cost and benefit estimate. NPV calculations are not calculated until the

summary tables are the sum of the initial investment and the discounted cash flows in each year.

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