Data Ladder software review: Data Ladder is a data quality software company that makes data quality tools affordable and really easy to use. Their data cleansing specialists are very knowledgeable and walk you through the process of getting data sorted and matched. They always seem to be evolving and updating their software to meet the needs of their clients. Their full-scale offering, DataMatch Enterprise, is not only faster than a lot of tools on the market today, but it also offers address validation and geocoding services. The price of their software is also within reach too for most small businesses.


The Big Bad Wolf of the Business World

What is Big Data? Well, that depends who you ask.

According to Wikipedia: Big Data is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing application.

According to O’Reilly Media: Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the structures of your database architectures. To gain value from this data, you must choose an alternative way to process it.

According to Doug Laney from Gartner: High-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.

Mike Gualtieri of Forrester says: Big Data is the frontier of a firm’s ability to store, process, and access (SPA) all the data it needs to operate effectively, make decisions, reduce risks, and serve customers.

McKinsey’s definition: Datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze.”

IBM defines Big Data with 4 ‘V’s.


Even though there is no single definition for Big Data that is universally accepted, there are some common concepts that almost all seem to converge on. And they are:   

  • Big Data is data has large volume (> 1 Peta bytes)
  • Big Data is data is not a single type i.e. structured and a variety of structured, unstructured etc.
  • Big Data is data that is being generated at a much faster rate than data in the past from all kinds of sources including social media.
  • Big Data is data that requires newer ways to store, process, analyze, visualize, and integrate.

More importantly however, we must consider what is BAD DATA…What is Bad Data?

Many organizations struggle with the accuracy of data for day-to-day decisions. Bad Data refers to information that can be false and completely misleading. Unfortunately, no industry, organization, or department is immune to it. If not acknowledged and fixed early on, bad data can cause serious problems. The complexity of Bad data goes far beyond structured customer data. To start fixing the data quality, you need to know what exactly caused the bad data:

  • Missing Data: Empty fields that should contain data.
  • Wrong or inaccurate data: Information that has not been entered correctly or maintained.
  • Inappropriate data: Data that’s been entered in the wrong field.
  • Non-conforming data: Data that hasn’t been normalized as per the system of records.
  • Duplicate data: A single Account, Contact, Lead, etc. that occupies more than one record in the database.
  • Poor data entry: Misspells, typos, transpositions, and variations in spelling, naming or formatting.

“Fortune 1000 enterprises will lose more money in operational inefficiency due to data quality issues than they will spend on data warehouse and customer relationship management (CRM) initiatives.” – Gartner

Bad data affects the entire revenue cycle of an organization, and will creep into your marketing and CRM systems. The impacts range can be catastrophic:

  • Failure of your marketing automation initiatives
  • Dissatisfied sales and distribution channels
  • Higher spam counts and un-subscriptions
  • Negative publicity on social media
  • Misinformed OR under-informed decisions
  • Invalid reports
  • Lower productivity
  • Loss in Revenue
  • Higher consumption of resources
  • Higher maintenance costs
  • Errors in product/mail deliveries
  • Lower customer satisfaction and retention
  • Increased churn rate
  • Distorting campaign success metrics

Consider this figure: $136 billion per year. That’s the research firm IDC’s estimate of the size of the big data market, worldwide, in 2016. Another number: $3.1 trillion, IBM’s estimate of the yearly cost of poor quality data, in the US alone, in 2016.

The reason bad data costs so much money is that decision makers must bring it in their everyday work and doing so is both time-consuming and expensive. If the data they use has plenty of errors, it can lead them into a dark journey of uncertainty with a flicker of hope.

Information and data are the most strategic assets of an organization. The Data Warehousing Institute reports, “Intellectual capital and know-how are more important assets than physical infrastructure and equipment.” It is critical to harness business data for effectual decision-making, and it must be as accurate as possible.

Big Bad Data used to be the Big Bad Wolf of companies around the world. A box that you dare open. However, over the last five years, there has been some leaps and bounds out of the private sector bringing faster and more accurate deliveries. One that is leading the pack is a company out of Suffield, CT called Data Ladder. They have brought some of the fastest result driven data in the industry as the first entries begin to show within the first few minutes of application. Data Ladder’s cutting edge software was architected by a group of data specialists who have over 500 years of combined data experience. This team has developed a software solution with an extremely high accuracy rating accompanied by impeccable speeds, according to favorable reviews. Furthermore, Data Ladder has a great trial software so you can try it before committing.

Data cleaning, matching and verification will continue to be a top goal for all major players across every industry as the data itself leads to growth and higher bottom-line revenues. Business executives, Analysis’ and Lead Generation Consultants are now pinpointing clean data for all effective marketing efforts. Companies are only as good as their data and must begin to be pro-active immediately. Do your company a favor and begin tackling your data imperfections by utilizing new technology in data cleaning.