Big Data. Big Decisions
InformationWeek
Special Coverage Series


How Oracle Helps Polk Decode Car Buying Secrets

An Overdue Move

(Page 2 of 2)

10 Lessons Learned By Big-Data Pioneers
10 Lessons Learned By Big-Data Pioneers
(click image for larger view and for slideshow)
When Polk finally made the decision to upgrade last summer, you could say the move was overdue. By that point the toughest multidimensional queries--those requesting demographic buyer insight within specific regions and dealer zones--were taking as long as three to five minutes.

The first wave of database migrations from a conventional RAC environment onto an Oracle Exadata Database Machine X2-2 half-rack took about four months, according to Miller. An immediate benefit was storage efficiency, thanks to Exadata's hybrid columnar compression. As an example, the Polk Insight database that previously housed about 2 terabytes compressed down to about 600 gigabytes. Performance instantly improved without any Exadata-specific performance tuning.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

"Initially we didn't do anything other than migrate the databases, and all the legacy queries and reports started running dramatically faster," Miller said, on the order of 10 times faster, he added.

Polk chose a capacious half rack with consolidation and room for growth in mind. Since the initial wave last fall, Polk has migrated multiple databases totaling about 22 terabytes out of conventional RAC deployments. On Exadata, compression has brought those stores down to about 13 terabytes. Among the tricks the company has employed is careful sorting of data before loading, a step that helps improve database performance.

"Exadata builds storage indexes automatically, and if you can lump the data that goes together, the index knows exactly where to find the data you're after," Miller said. If you sort data by zip code, for example, the database knows just where to find the data needed for a query by geography and it will run that much faster.

Polk is also making extensive use of materialized views, which effectively store often-requested query results for rapid recall. Exadata's compression has helped reduce the size of materialized views and supported more sophisticated views, said Miller, and that has reduced the number of table joins that have to take place in real time. This, too, improves performance, even when exploring multiple dimensions of data.

"If a customer wanted to look across multiple dealer zones and then start bringing customer demographics and data such as lease versus purchase, that would have taken as long as two to five minutes in the old environment," Miller said. "In Exadata these sorts of queries are running in 10 seconds."

Polk's Exadata migration is still in progress, but to date it has consolidated nine separate databases down to four and eliminated eight out of 22 production database servers. Polk has yet to move the other half of its data still in conventional deployments, but it expects to consolidate on a total of 10 servers.

Improving Insight

Polk had some 10,000 custom reports built in Oracle Discoverer before the Exadata migration began. With an upgrade to Oracle Business Intelligence Enterprise Edition (OBIEE), Polk is now delivering user-customizable dashboards that used to require custom development work. This has greatly improved productivity at Polk.

Customers now take advantage of OBIEE threshold and alerting capabilities so they can review dashboards when certain conditions are met, rather than having to review reports and look for notable changes.

OBIEE has ushered in new types of reports. For example, the suite taps Oracle 11g-managed spatial information to map data geographically. Thus, manufacturers can see customer and model counts projected onto maps, with five-year trends and competitive insights.

"We can use shading to indicate market-share gains and losses," said Kelly Garcia, Polk's VP of global application development. "They can instantly see whether they are up or down in a particular region."

There are areas where Polk is still taking a wait-and-see stance where Oracle capabilities are concerned. For example, several Polk customers have equipped or want to equip their field reps with Apple iPads for email access and dealer interaction, but Garcia said Oracle's current iPad release is just a start.

"We're unclear whether we're going to go with that product because you can't rebrand the interface, as we may need to do," he explained. "If a customer really needs a way to get our data on the iPad, we can give it to them, but it's not very interactive and we'd like to see more capabilities."

As was the case with Exadata, Polk seems content to communicate what it wants in an iPad release to its incumbent vendor and to wait a bit--say to a 2.0 version--to get what it wants.

In the new, all-digital issue of Network Computing: Microsoft and Citrix are closing the gap with VMware. Before you roll out the latest edition of vSphere, reconsider your virtualization platform. Download the issue now. (Free registration required.)

« Previous Page | 1 2  


Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.