Most of you have probably heard the term “Big Data”.  It is a trendy buzzword at many conferences and there are a number of articles and blogs that discuss it as the next big thing.  What exactly is “Big Data” and why should you care?   Most define it as the collection and analysis of large amounts of data to make better decisions and/or provide better direction.   To me, the term speaks to the growth in transactional and other data processing over the past 10-15 years (ex. – Amazon’s recommendations for similar products).   There is much more data available today, which can allow for more precision in BI (Business Intelligence) and other types of analysis.

The problem is that “Big Data” is not the answer.  Quality Data is the answer.

Quality does not seem to be a focus in any of the articles I’ve read recently.  “Small Data” can be even more powerful than “Big Data” depending on the quality of the data being captured.  While it is true that more data can lead to more precision in analysis, the data elements must be clearly defined and validated.  By clearly defining what is important in terms of data capture and developing mechanisms to validate the data, you will ensure that quality data flows through the process, no matter the size of the data.

Altair has 70+ years of combined processing and analytics experience and a scalable network infrastructure so we can help your company navigate any data considerations.  The average company processes 63 Terabytes of data annually.  As a data-centric company, Altair processes nearly as much data on a monthly basis.  Please contact me at tblackman@altairci.com to learn how Altair can help.

What is the match rate? This is the first question I hear when appending data for a customer. But is it the most important question?

Assuming your vendor is standardizing the names and addresses on both datasets to ensure the most matches, how do you know the appended data is matched properly? There are many possible match levels – address only, last name + address, full name + address or phone number. The type of data determines how to match.

In most cases, matching should follow this loose guideline:

-          Deed/Mortgage/Demographic matching  should be done at the household level

-          Tax/AVM/home value matching should be done at the address level

If your vendor is matching at different levels to the same file, you could be receiving false matches depending on the type of data you’re using. Ask your vendor to flag the different types of matches so you can determine yourself which appended elements make sense and at which match level. Ultimately, the match rate is important, but the way the match is done is paramount.

Altair has several enhancement databases available to supplement data element population totaling more than one billion current and historical records. We have the experience and data to assist in providing the highest quality matching for overlay/append projects. Please contact us to learn how Altair can help.

A recent study by University of California, San Diego (UCSD) indicates data processing has increased dramatically in the past several years and continues to grow at the rate of 30-40% annually. Transaction processing amounted to 44% of data processed last year.

An example — A book purchase from Amazon entails much more processing than the simple sale transaction. People who purchased the same book may have bought other items that may be of interest. These items are suggested as something you may like better, or may like in addition to the item you are considering. This is accomplished by matching to previous transactional data to see what others have purchased. The increase in processing will only continue as location-based data is added to transactional data.

Altair has over 70 years of combined processing and analytics experience, and a scalable network infrastructure, so we can help your company navigate the processing explosion. The average company processes 63 Terabytes of data annually. As a data-centric company, Altair processes nearly as much data on a monthly basis. While your data may have unique content, the processing hurdles are familiar to Altair and we have systems in place to handle it. Please contact us to learn how Altair can help.

http://hmi.ucsd.edu/howmuchinfo_research_report_consum_2010.php

While doing some research for one of our clients, questions came up about zip code facts.  The United States Post Office (USPS) operates one of the largest infrastructures in the world but finding information on the system can be difficult.  In the spirit of sharing, here are some of the facts that Altair uncovered.

Do P.O. Boxes have their own zip+4?

YES

How many zip+4s are in the United States?

33,182,405

What is the average number of zip+4s within a zip code?

863.5

What is the lowest number of zip+4s within a zip code?

1

What is highest number of zip+4s within a zip code?

7,284

What are the average number of households within a zip+4?

4.5

What is the highest number of households within a zip+4?

4,584

What is the lowest number of households within a zip+4?

1

Each year up to 20% of your customers move. It’s a proven fact that new movers buy more products and services and are more likely to establish new buying relationships than established consumers. With the daily and weekly tracking of new movers through phone connects, utility connects, deed recordings, and other sources, many companies use this opportunity to identify valuable new prospects.

Now consider your own database of customers. Your competition is able to identify new movers, or your clients that are moving, within 3 to 5 days of their move. To stay ahead of competitors, you should apply frequent National Change of Address and new mover updates. The first step in understanding your customers is to develop good data hygiene practices that you can apply to your customer data at least every month and preferably every week.