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    Data Cleansing vs Data Maintenance: Which One Is Most Important?

Data Cleansing vs Data Maintenance: Which One Is Most Important?

There are always two aspects to data quality improvement. Data cleansing is the one-off process of tackling the errors within the database, ensuring retrospective anomalies are automatically located and removed. Another term, data maintenance, describes ongoing correction and verification – the process of continual improvement and regular checks. Often, businesses ask us: which process is the most important? In the long term, which one should we focus on? Unfortunately there is no simple answer, but there is an easy way to understand the differences between them. An Apple A Day… When we think about data, we can compare it to caring for our health. In particular, data maintenance is a lot like brushing your teeth. We brush our teeth at least twice a day to stop decay from taking hold. If we didn’t, the sugar that we consume would gnaw away at the enamel and cause rot to set in. The longer we leave it between brushings, the more vulnerable our teeth become. Similarly, our database must be continually cared for and maintained. Why? Data in a database rots and decays in […]
By |August 25th, 2015|Data Cleansing|Comments Off on Data Cleansing vs Data Maintenance: Which One Is Most Important?

Defining Your Data Quality Problems

To tackle any problem in a systematic and effective way, you must be able to break it down into parts. After all, understanding the problem is the first step to finding the solution.  From there, you can develop a strategic battle plan. With data quality, the same applies: every initiative features many stages and many different angles of attack. When starting a data quality improvement program, it’s not enough to count the amount of records that are incorrect, or duplicated, in your database. Quantity only goes so far. You also need to know what kind of errors exist to allocate the correct resource. In this interesting blog by Jim Barker, the different types of data quality are broken down into two parts. In this article, we’ll look closely at defining these ‘types’, and how we can use this to our advantage when developing a budget. Types of Data Jim Barker – known as ‘Dr Data’ to some – has borrowed a simple medical concept to define data quality problems. His blog explains just how these two types fit together, and will be of interest to anyone who has […]
By |August 5th, 2015|Data Management|Comments Off on Defining Your Data Quality Problems

Can Businesses Profit From Data Quality?

We often refer to business data as an asset. Something as prized as data is important for every function in an organisation, so it’s easy to see why it’s so valuable, and vital. On our blog, we’ve discussed ways that clean data can make an organisation more efficient, and therefore more profitable. And we know that clean data cuts waste. But data is not just an asset internally. Some businesses actually deal in data. They trade it, sell it and market it to other businesses. This kind of activity requires pristine data quality and a commitment to continuous management. Profiting from data is not simple, though, and businesses are learning that there are boundaries. Before advancing plans to turn data into riches, there are some basics that must be considered first. Selling and Accumulating Data Organisations that sell data have had some bad press recently. Perhaps the biggest scandal can be accredited to the NHS, which has sold private patient data unlawfully to insurance companies and researchers. The NHS still sells patient data, but it now has to be clear […]
By |July 8th, 2015|Blog, Data Quality|Comments Off on Can Businesses Profit From Data Quality?

Taking Control of your CRM Data

CRMs are supposed to be used to achieve better efficiency. By investing time in the CRM, sales teams should be able to identify leads, retain existing customers and successfully recruit new clients to the fold. Your research and development team should be able to use the metrics from the CRM to drive next year’s products, and the marketing team should be able to feed this back into their campaigns next year. Sadly, many CRMs fail to perform well. No system could feasibly solve every problem in your business, but if the CRM is creaking under the weight of dirty data, it could actually be hindering progress. Not an Afterthought We’ve heard estimates of CRM project failure rates between 30 and 60 per cent. And when you consider that the cost of a CRM starts at hundreds of pounds per month, the potential for waste is enormous. That’s not counting the cost of implementing the CRM, including change to systems, processes and workflows. After all of that cost and investment, it can be extremely disheartening to find that staff simply don’t trust their data. The greatest success in data quality comes […]
By |June 16th, 2015|Blog, Data Management|Comments Off on Taking Control of your CRM Data

Data is Immortal, but Not Immune to Decay

Data exists in a dangerous state of near-non existence. Few businesses would risk not having backups in place. With cloud computing becoming commonplace in enterprise, we’ve come to accept that our data will be replicated and stored in duplicate. Even data that is intentionally deleted can often be recovered. When Yahoo! purchased Geocities, nobody dreamed that it would go ahead and delete the entire archive – more than 600 gigabytes of internet history. Despite this, enthusiasts were able to quickly archive the collective work of 35 avid Geocities webmasters – an important milestone in our ability to breathe new life into data that someone else does not want. The Cost of Deletion Deleting data is not just a catastrophe for the user, or the business, or the system itself. Deletion of data also has a cost attached. We’ve all deleted files, essays, reports or emails by accident, and we’ve been forced to spend hours recreating what we lost.  Other consequences also make data loss costly: loss of custom, loss of reputation, or damage to a brand. Often, it is easier to harvest massive amounts of data, and […]
By |June 2nd, 2015|Blog, Data, Data Quality|Comments Off on Data is Immortal, but Not Immune to Decay

Were the Election Polls Marred by Poor Quality Data?

The UK’s general election took place last week, on Thursday 7 May, 2015. It was an election that had been hyped for being ‘too close to call’. According to the polls, the government was likely to be a coalition of one or more, with no party achieving a majority. It could have gone either way.   Imagine the shock when the BBC announced the exit poll results: a landslide victory for a single party – the Conservatives. Election polling companies are reliant on various types of data to come up with accurate predictions. Like any business, they must apply quality control to their data. They must cleanse it, eradicate errors and duplicates, and ensure their contact records are up to date. They need to ensure they don’t call the same person twice, and they must encourage people to give accurate data in response. How could so many companies get it so badly wrong? And was the data at fault, or was there another gremlin in the machine? Precedents in polls This is not the first time that polling data has let down the public, politicians and press. During […]
By |May 12th, 2015|Blog, Data|Comments Off on Were the Election Polls Marred by Poor Quality Data?

Do Your Customers Hide Their Data?

Personal data has an image problem. People are increasingly wary of handing over their details to websites – particularly when they have no intention to engage long term. Many marketers set out to obtain email addresses, yet do very little to ensure the email addresses they get are valid. This is the beginning of a vicious circle for the business they’re working for. Why? Trust has broken down. If customers don’t trust you, they will hide their data from view. Official advice from tech-savvy gurus is to hide your real personal data from the prying eyes of advertisers, by entering false dates and other booby traps. In 2012, this advice was even given by the UK government as a way to protect security and stay safe online. This is a dirty data nightmare for small businesses, and it will only serve to compound the considerable problems we already face with bad data. Where We Are Now According to the Telegraph newspaper, half of British consumers think their data is at risk. They cite data loss, theft and surveillance – all key issues that have hit the […]
By |April 28th, 2015|Blog, Data, Data Services|Comments Off on Do Your Customers Hide Their Data?

Enhance your CRM Data to Sharpen your Sales Pitch

In the old days, you knew who to contact to make business. There were a few job functions, and a few levels of seniority. A name with job function was usually enough for you to hit the bullseye more often than not. But as businesses diversify and become more complex, this becomes more difficult; and even for the “data-aware”, old habits die hard. I had an interesting conversation this week with a potential business partner I was trying to reach out to. This was an organisation that I had done a bit of old school research on, understood their target market and modus operandi as best I could from their website and LinkedIn, and decided that it was definitely worth investigating further. So with my “sales research” head on, I made the call to their London office with a name & job role in my hand that I thought would give me more information and might be able to progress the idea of a partnership. When researching, I always start with people who can give me the most […]
By |April 8th, 2015|Blog, Data, Data Management, Data Quality|Comments Off on Enhance your CRM Data to Sharpen your Sales Pitch

How a Chief Data Officer Can Make Your Data Great

How a Chief Data Officer Can Make Your Data Great Fresh data is usually pristine. It’s data in it’s clearest, most accurate form – straight from the customer or client. If you’ve put measures in place to cut back on data input errors, such as form validation, you can be reasonably sure that the newest records in your CRM are the “latest and greatest”. If your CRM has been active for some time, you’ll have a number of older records that have accrued. These records are the ones your sales and marketing teams will rely on when it’s time to approach existing customers and sell to them again. Chances are, the quality of these records will be fairly good, but it will have fallen since they were first collected. As data quality slips, data goes from “great”, to “good”, to decidedly “bad”. Waste and Cost Data management is a huge cost to businesses, but it’s the bad data that is the real drain. According to Gartner, the average business wastes as much as $13.5 million sorting out data quality problems every year. Poor management is rife.
By |March 25th, 2015|Blog, Data, Data Quality|Comments Off on How a Chief Data Officer Can Make Your Data Great

Data Quality – Supporting Your Sales Team’s Unnatural Disposition

I should start by saying that I love data – or more importantly I love the information that data can unveil to an enquiring mind. I am seldom happier than when I am looking for trends in whether salespeople decide to make more telephone calls straight after the sales meeting on Tuesday afternoons, what the average sales cycle is for Widget A versus Thingummy X, and if there is a correlation between customer spend and activity. I could spend hours in there, figuratively speaking. However, I’m afraid I am a walking cliché – a sales professional with a natural disposition to spend as much time as possible talking to clients, and as little time as possible in the “non-revenue-generating” task of capturing the correct and complete data in my CRM system. Salespeople don’t do attention to detail, right? They are the hunter-gatherers who stalk the beast, slay the beast, bring the beast back home and put it on the fire they made. Someone else can do the washing up. If they did attention to detail, they’d work in […]
By |March 18th, 2015|Blog|Comments Off on Data Quality – Supporting Your Sales Team’s Unnatural Disposition