Upcoming data webinar series

Published on August 11, 2010 in data integration. 0 Comments Tags: , , , , , .

We are excited that David Loshin, President of Knowledge Integrity, will be collaborating with us this fall on a series of webinars and learning opportunities.

 The first event, slated for Wednesday, September 8, covers Data Integration Alternatives—Managing Value and Quality.

With data volume growing at an alarming pace, it has never been more critical for organizations to manage data and maximize the value of this information.  Over the years, most companies have gotten good at creating transactional and operational business applications, but these disparate systems have led to virtual “islands of data.”

On the other hand, there is a growing list of enterprise applications (such as business intelligence and data warehousing, customer relationship management, enterprise resource planning, and even more complex approaches to business analytics) that require access to data sets from a variety of sources.

 In this environment, data centralization has become critical.  In this upcoming webinar, we will discuss the options and alternatives available to you today that can help you become a master in data sharing. Topics to be covered include:

  • Exploring Data Integration Alternatives – from traditional ETL (Extract Transform Load) to Data Virtualization
  • Understanding Data Integration Challenges – including completeness, consistency and reasonableness
  • Adding Value to Data Integration – using governed data quality services

This informative webinar event is scheduled for Wednesday, September 8 @ 11AM ET (15:00 UTC/GMT) and is offered by Pitney Bowes Business Insight at no cost to you. Please take a moment to register today.

Best Practices in Geocoding

Published on August 11, 2010 in Data Quality and Geocoding. 0 Comments Tags: , , , , , , .

As more than 70% of all business records include a location component, it is not surprising that location accuracy has become such an important part of data quality. Today, organizations are using location data to administer market analysis, risk assessment, effective targeting, network investments, site selection and portfolio management.

Before you can analyze, extrapolate or profit from location data, you first need to associate each record with an accurate latitude and longitude coordinate. That’s why so many organizations employ geocoding. Geocodes translate common reference points, such as customer addresses, into latitude and longitude coordinates that makes it easier to analyze data.  If your geocode is wrong, however, your analytics are wrong, your insights are wrong—and your decisions are wrong—so it pays to be accurate.  Today’s best practices include: 

1. Validate source addresses

Geocoding tools should offer the ability to cleanse data, standardize addresses and validate that source addresses are correct before applying geocodes.

2. Validate geocode results

Accuracy has another element, positional accuracy, which measures how close the geocode is to the reference point. Geocoding an address to the center of a city, for example, will be less positionally accurate than one centered on a precise parcel or rooftop.  Today’s leading solutions provide a ‘geo-confidence index’ that estimates the probability that the latitude and longitude assigned correspond to the place intended. 

3.   Utilize precise, up-to-date reference data

How often you update your reference data is important, as reference points such as roads, addresses and developments are always being added and modified. Many companies do quite well with quarterly data refreshes.

4.   Geocode to multiple levels of accuracy

There will be times when it is not possible to deliver a geocode centered on a specific address or parcel.  The tools you use should recognize this and apply consistent rules, automatically cascading to the next most-specific point of reference, from address point, to street level, to postal code, city, state, etc.

5.  Combine geocoding and spatial analysis

Ultimately, the goal of any solution is to provide answers, not latitudes and longitudes.  Look for tools that combine geocoding with the ability to perform analysis, calculations and predictive analytics, such as point-in-polygon analysis, closest site analysis and the ability to calculate drive time and distance.

 6.  Integrate into existing workflows

When you can integrate geocode analytics into existing operations and business processes, you can which streamlines workflows, eliminate manual processes and improve decision making. 

 7.   One-stop service

Solutions need to be simple to use and flexible enough to meet different business requirements. A single technology platform that matches up with your overall corporate objectives can help ensure that a consistent standard will be applied in every market.  Likewise, maintaining one platform reduces cost of ownership and can speed up system integration. A single interface also simplifies training and education, and makes it easier for your company to gain the skills and capabilities in Location Intelligence needed to achieve a competitive advantage.

 To help you learn which geocoding solutions are available in your area, Pitney Bowes Business Insight has created a multi-media map.  You can use the interactive map to get detailed information for each country regarding our address correction, geocoding and routing capabilities.

More actionable data

Published on June 8, 2010 in Data Governance, Data Quality, Geocoding and Spectrum Technology Platform. 0 Comments Tags: , , , .

Business users count on high-quality data every moment of every day.  

In practical terms, data needs to be “fit for use”.  That is, you data should add value to your existing operations and help users make better, more accurate decisions in the course of doing business.  For most organizations, ensuring that data is fit for use entails three distinct disciplines. 

  • Traditional data quality: the ability to cleanse, standardize and validate data
  • Location intelligence: the ability to see data in context of location
  • Spatial analysis: the ability to understand the relationship between two or more data points

Today, 70% of all records contain a location element and knowing “where” affects decisions in virtually every aspect of an organization.  Consider:

  • Marketing can gain insights into customer needs and buying habits
  • Insurance underwriters can identify potential risks (such as proximity to a flood zone)
  • Finance teams can assign proper tax jurisdictions
  • Sales managers can develop territories based on true market opportunity
  • Service teams can plan routes to minimize logistics costs
  • Facilities managers can develop optimal network strategies

Location and spatial analysis are so critical, in fact, that organizations are increasingly looking to incorporate geocoding, location intelligence and predictive analytics as part of their core data quality platforms and processes.

This month, Navin Sharma, our Director Global Product Strategy, will share how these market realities play out in the latest release of the Spectrum™ Technology Platform.  This informative webinar will include details on how you can integrate enterprise geocoding, location intelligence and a new geo-confidence model into your core CRM, ERP and legacy systems.  Ideal for data stewards, IT managers and business users, I invite you to register for this Webinar today and get the facts on today’s best practices in data quality, data management and more.

When BI and ETL meet

Published on June 8, 2010 in data integration. 0 Comments Tags: , , , .

Business users and data analysts face two daunting obstacles when it comes to making decisions. First they need to access accurate, timely data.  Then they need to manipulate this information to create meaningful insight.  Increasingly, organizations have found that it’s advantageous when they can tackle both of these challenges at once.

ETL, the short-hand for extract, transform and load, is the backbone of data integration.  This process makes it easy to extract information from multiple sources and transform this data into a consistent, usable format that can then be loaded into a database, data warehouse or data application.  For example, the right tools can read data in its native format from CRM, ERP and legacy systems without needing to write custom programs—and then combine this information to create a 360-degree view of your customers.

BI, or business intelligence, involves analyzing this business data to generate the insights needed to make more effective business decisions.  When you can turn data into meaningful information and useful reports, you empower business users to respond quickly, with confidence.

While ETL has traditionally been an IT function, BI comes to life when managed within the lines of business. Recognizing the need for speed and efficiency, today’s leading-edge technologies combine integration and analytical tools into a single interface that is easy to use and understand.  Designed specifically for business users, now analysts and other decision makers can pull together the necessary data without expensive IT overhead.

Scott Arnett, Product Strategist, shares some details on how Pitney Bowes Business Insight brings together Business Intelligence and ETL in a single platform.  This Webinar will focus on the latest release of Sagent Data Flow, which is built specifically for business users who need to efficiently integrate data from a variety of sources as well as perform analytics.  Take a moment to register today.

Hot data trends in telecom

Published on March 30, 2010 in Data Governance, Data Quality, Geocoding and data integration. 0 Comments Tags: , , , , , , , , .

In recent months, many in the communications industry have identified new ways to increase profits via data quality and location intelligence.  We’ve compiled the best resources all in one place, from customer activation, cost-effective service and event-driven intelligence to customer relationship management, broadband expansion and gaining a handle on wireless coverage.

Trends in Customer Activation: Complexity and competition have raised the stakes of the onboarding process, a time when companies can lock-in customer relationships, tackle the high cost of fraud and cross sell most effectively. New technologies—particularly in the area of data quality and integration—now provide for more efficient and effective customer activation programs.

Broadband Expansion: To the Stimulus and Beyond. Communications executives and state agencies discover how new data technologies provide insights to secure funding, improve service and expand their business.

Five Must-have Capabilities for Unbeatable Customer Care. As quality customer care becomes an even more important factor in overall profitability, communications companies will need to identify where they can make the biggest impact.

Event-Driven Intelligence in Telecommunications. The latest corporate mandate provides carriers the practical insights they need to transform business processes for the better.

Data, Disconnected. Communications firms take the necessary steps to build greater accuracy into their customer management processes.

RF Propagation Coverage Data. Processing data for optimized display and analysis in a web-based application.

Patterns in data quality

Published on March 30, 2010 in Data Governance, Data Quality, Data Stewardship and data integration. 0 Comments Tags: , , .

Every company relies on data in different ways to support unique workflows and processes.  While the data universe may vary greatly, patterns in data quality cut across functional and departmental lines.  In all cases, improving data quality can enhance the value of business information for both operational and analytical purposes. 

Data quality services should be a common architectural resource, with consistent and repeatable data interpretation and measurement.  These services should be easy to understand, simple to use and deployable in minutes. 

All of this can be achieved through a well considered organization of data quality services.

With Patterns in Data Quality, a new PBBI White Paper, you’ll discover a method for organizing data quality services in a Service Oriented Architecture.  Learn about the patterns in data consistency, uniqueness and accuracy – and how data administrators can leverage these patterns to manage data enterprise wide.

Data integration video tours

Published on March 30, 2010 in data integration. 0 Comments Tags: , , , .

Our product team has recently put together a series of videos that make it easy to learn about data integration and how our Sagent Data FlowTM solution can help you achieve more in your organization.

Got a minute?   Product Strategist Scott Arnett provides a quick introduction to data integration and Sagent Data FlowTM.

Ready to dig deeper?  Here, Arnett provides a more comprehensive look at the core functionality of Sagent Data FlowTM.  Learn what you, as an analyst or developer, can do with this solution.  Discover the dramatic impact it can have on your current Business Intelligence and Data Integration needs.

Take a test drive.  This self-play demo takes you through real-life examples, so you can see the unique tools and benefits associated with Sagent Data Flow.

Enjoy the tours!

Battling today’s global threats

Published on January 27, 2010 in Data Governance and Data Quality. 0 Comments Tags: , , , , , , , , , , .

Do you really know your customers?

Will someone try to defraud your business? Use their account with you to circumvent laws? Threaten your customers? Left to your own devices, it may be difficult to ascertain the true intentions of everyone who wants to be your customer.

To support this initiative, government agencies across the world have created watch lists to help identify individuals who may represent security risks. At the same time, the same governments often require companies to collect, validate and match key information related to a customer’s identity to support the global fight against terrorism, fraud, money-laundering and identity theft.

While anti-money-laundering requirements may only affect financial institutions, the broader requirements impact most every business.  Compliance with the USA Patriot Act, Red Flag Rules, Bank Secrecy Act, HIPAA and Sarbanes-Oxley, for example, all require a more accurate, more in-depth view of your customers.

Data quality is often the first line of defense.  For executives in charge of compliance, poor data can result in the company facing public embarrassment, damage to brand equity, significant fines and even lawsuits. 

Technologies such as Pitney Bowes SpectrumTM help automate the customer screening process with robust matching and scoring mechanisms.  Such solutions consolidate various agency and country lists – providing a single source for matching against both third-party and internal fraud databases.   

In any case, whether your company treats this as a security concern or a compliance issue, your company’s data steward may be the one person best equipped to mitigate the threat.

Data and the CTO Edge

Published on January 27, 2010 in Data Governance, Data Quality, Data Stewardship and Spectrum Technology Platform. 0 Comments Tags: , , , .

IT executives no longer need to be convinced about the high cost of poor data. Most will freely admit that customer records are incomplete, not always consistent, rarely consolidated and frequently contain errors. Each day, however, brings new challenges, new business requirements and time-of-the-essence business demands.

In a recent CTO Edge Corner podcast hosted by Mike Vizard, Jay Bourland from Pitney Bowes Business Insight explains how IT organizations need to bring good data governance practices to bear if they ever want to get a real handle data quality. 

I would like to invite you to take a few minutes this week to listen in as Mike and Jay discuss how some IT execs are dealing with long-overlooked challenges. For example:

  • Juggling access and security. Data becomes more valuable when accessible by more people, but every new approved user represents a threat to data quality and privacy.
  • Responsibilities for data governance. Is it a committee? A person?  Is this an IT function or something everyone needs to be accountable for?
  • Relationship between IT and business units. Where in the process should business users engage IT, and vice versa?  The good news is, effective collaboration is attainable.
  • Organizational roadblocks. Are data profiling, cleansing, updates, governance and integration all managed by the same person on the same schedule? If not, you can still get everyone on the same page.

In addition to these insights, Mike and Jay also touch on the capabilities organizations should look for to achieve the greatest ROI.  If you want to get more practical, you will also want to catch the new 8-minute data quality video from Kit Hamilton that outlines the day-to-day and business challenges and an innovative three-step solution.

10 ways to maximize value of customer data – Part III

Published on January 21, 2010 in Data Quality and Spectrum Technology Platform. 0 Comments Tags: , , , .

In 2010, many business initiatives will bring attention to data quality, as the completeness and integrity of customer information can have a clear impact on near-term profitability.  Previously, we examined how data quality affects marketing and operational efficiency.  Today we focus on compliance and risk management.

8. Risk Management. While companies in the insurance, financial services and healthcare arena may face new regulatory oversight when it comes to risk management, organizations of all sizes will be looking for ways to mitigate risk in these uncertain economic times—especially when it comes to compliance.  Million dollar fines, ongoing lawsuits and damaged reputations are just a few of the costs that can be mitigated when companies have confidence in their customer data.

9. Tax Management. With states and localities dealing with budget pressures themselves, there will be increased scrutiny on how businesses assess, collect and manage tax obligations. Unfortunately, tax jurisdictions change frequently, and jurisdictions are not aligned with ZIP Codes or U.S. census data—so companies will look to specialized applications in order to keep pace with ongoing changes, comply with government requirements and avoid penalties.

10. Fraud Detection. One effect of the recent recession is an increase in fraud. Many companies, including those in the financial services and insurance industries, are looking for ways to integrate fraud detection applications into their core business processes. Here, data standardization, address validation, location intelligence and the ability to match against “watch list” files can greatly reduce risk and exposure.

Whether your organization is looking to pursue one, two or all ten of these strategies, Pitney Bowes offers solutions that can help, including our SpectrumTM Technology Platform.   As we start 2010, think about the ways you can leverage data quality to locate new opportunities, connect with customers and communicate more efficiently.