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Data quality management is highly dependent on people and processes, but increasingly, companies are also beginning to incorporate data quality technology into their data quality management strategies. Founded in 1997, Data Ladder is a leading provider of quality and data cleansing solutions that many of these businesses turn to. Learn more in this comprehensive Data Ladder review.
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What is the data scale?
Data Ladder is a leading provider of data quality solutions, specializing in data cleansing features. Services and products offered by Data Ladder, such as DataMatch Enterprise, enable companies to get the most out of their data through data deduplication, data profiling, data matching and enrichment operations Datas.
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Projects delivered by Data Ladder include Data Quality Management, Modern Data Cleansing, Entity Resolution, and Address Verification. Data Ladder customers include Fortune 500 companies such as GE, HP and Deloitte. The services offered by Data Ladder are categorized into professional services, training and certification services, implementation services, and bespoke programs.
Key Features of Data Ladder
Data import
Data Ladder offers an all-in-one solution for connecting, importing and combining data from isolated data sources in a business environment. This includes data from different types of cloud storage, local files, relational databases, APIs, and file formats. The seamless data import process ensures that all data sources are connected to the application, regardless of the format or source of the data. Data Ladder uses an ODBC (Open Database Connectivity) interface for importing data.
Data profiling
Data profiling refers to the process of examining data to understand how it is structured and discover details about the content of data sets. Data Ladder provides a 360° view of data through its industry-leading data profiling tools that can be used to identify data types, data patterns, and empty values while flagging opportunities for data cleansing.
Data cleaning
One of the main differentiators of Data Ladder is its data cleansing tools, which can be used to remove duplicate, empty and invalid data to achieve data standardization across all data sources. These tools can also be used to create and validate data models.
Data matching
Data matching is the process of comparing data to calculate the level of similarity. This process helps identify and eliminate data, especially for datasets that do not contain unique identifiers or foreign keys. Data Ladder provides data matching functionality to run data matching algorithms; data matching criteria can be customized based on individual needs.
Deduplication
Manual data deduplication can be time consuming and prone to human error. The deduplication tools offered by Data Ladder automate the process of finding and removing duplicate data records. Even if there are no exact values or unique identifiers, Data Ladder is able to find duplicate data. This is made possible by the advanced algorithms behind the Data Ladder tools.
Merge and Purge
The merge and purge functionality provided by Data Ladder enables the storage and integration of entity records. These tools help overcome structural differences between datasets, prevent data loss during merging and purging, and streamline data-driven decision-making.
Advantages and disadvantages
Advantages
Dada Ladder solutions are among the fastest and most reliable solutions on the market. The DataMatch application is able to work quickly even with large datasets. It can also load data tables extremely quickly.
Another key benefit of using Data Ladder is the user-friendly user interface (UI) and ease of use it provides, especially for DataMatch solution users. Although Data Ladder offers live training sessions and tutorials to get users started with their apps, several users reported that they only needed minimal training because the app interface is so simple.
The inconvenients
There are a few advanced features in Data Ladder that don’t have much documentation available on how to use them. This includes features for creating customer data profiling templates, advanced matching options, and setting up survival rules. Some users have also reported minor bugs in the data matching algorithm.
Data Scale Alternatives
WinPure
WinPure Clean & Match is one of Data Ladder’s main competitors. WinPure offers similar high speeds and accuracy in matching and cleaning data. It also offers advanced features including proprietary algorithms to detect data issues. Other main features include automatic selection of source data, tools to export results, merge and purge tools, and a dashboard for data match scores.
OpenRefine
Another great alternative to Data Ladder is OpenRefine, formerly known as Google Refine, which is an open source data quality and transformation application. It offers various data cleaning tools that can convert data formats and perform data matching. OpenRefine allows users to analyze data from the Internet and work on the data directly on their machines.
Trifacta
Designer Cloud by Trifacta is a data cleansing application available on-premises and as a cloud-based application. It is aimed at small, medium and large companies. The main functionalities of Trifacta include data cleaning, data validation, data structuring and data analysis. It also uses machine learning algorithms to recommend data transformations.
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