Low quality, dirty, and noisy data can create huge issues for any business. If you begin your analysis with dirty data, your downstream processes will be equally dirty, often completely unusable – to the point that they can actually be harmful to your organization.
Raw data, especially unstructured data, like text and images, is usually unusable for most types of analysis because it has to be formatted and cleaned, so that machines can understand it.
Data cleaning can be tedious, but it’s absolutely necessary to get solid insights and clean analyses.
Data scientists spend between 50% and 80% of their time collecting and cleaning data before it can be mined for insights – some say it’s even more important than building better machine learning algorithms.
And having data cleaning tools available can definitely speed up the process.
Let’s take a look at some of the top data cleaning tools that can take the pain out of cleaning and data preparation, so you’ll be set up for downstream success.
Take a look at some of the best data cleaning tools for your business and the benefits and drawbacks of each:
Formerly a Google SaaS product called Google Refine, OpenRefine is now open source with a number of extensions and plugins available. OpenRefine’s straightforward and user-friendly GUI allows users to easily explore and clean data without any code. But the ability to run Python scripts means you can perform more complex data filtering tasks and streamline processes to your custom needs.
One of the original “data wrangling” tools developed from Stanford’s Data Wrangler, Trifacta takes data cleaning to the next level. Trifacta guides users through processes to join their expert knowledge of their data with powerful AI for some of the best cleaning results available. Trifacta’s GUI has great built-in tools, like pattern anomaly highlighting, so you can quickly find misspelled words, formatting issues, and irrelevant data.
Tibco Clarity is a SaaS data gathering and cleaning tool that’s ideal for non-coders. Tibco Clarity allows simple integration from a variety of data sources and formats, so you can merge and clean all of your data together and output it in a single format. Once you have your cleaning processes configured, you can automate data collection, cleaning, and formatting to streamline operations. Easily detect data patterns and visualize trends and outliers, even if you don’t know a lot about your data.
RingLead is a SaaS, cloud-based platform for data arrangement and coordination that focuses on automating CRM processes and streamlining marketing efforts. It’s an end-to-end marketing analysis solution, rather than just a data cleaning and wrangling tool. But it offers great results for data gathering, cleaning, and enriching. The aim is to normalize CRM data to avoid duplications, effectively segment customers, and link leads to accounts.
Talend offers a number of tools for data evaluation, cleaning, and formatting. The Talend Trust Assessor quickly checks your data, before diving into cleaning, to ensure that it’s trustworthy and actually valuable for the analysis you want to do.
Talend Data Quality is their data integration tool to draw data from any number of sources and format for your needs. And their Data Preparation Solutions offer different techniques for data profiling, cleaning, and enriching in real time. Online reviews regularly point to Talend’s great integration with tools, like Salesforce.
Generally used for cleaning data and inputting into BI platforms, Paxata can be great for users who don’t know a lot of code, although reviews generally state that their UI is a bit lacking. Compared to tools, like Talend, Paxata is generally considered to be better at natural language processing (NLP) with “intelligent recommendations” to automatically indicate outliers, typos, and misspellings. And centralized data and shared workspaces make internal collaboration easy.
Cloudingo is a one-stop-shop for importing, cleaning, and preparing Salesforce data. The user-friendly dashboard allows you to set data scrubbing parameters – data deduplication, merge and convert data, mass update, and mass delete – and run it across all of your Salesforce data. It’s easily scalable and can run on huge amounts of data. Cloudingo’s automated processes mean you always have up-to-the-minute clean data right at your fingertips. As Cloudingo is mostly automated, a proper initial setup is crucial, but they’re known for great customer support.
Jupyter is an open-source platform that requires Python scripting but can handle the most technical and advanced data cleaning techniques on huge amounts of data. Jupyter Notebook allows you to run scripts and make use of Python resources (like regex operations) and other third party libraries – Spacy for NLP, Pandas for data frames, and matplotlib for chards.
The data cleaning tools you choose to use will depend on the kind of data you want to analyze and your downstream processes and goals. But it’s clear that you need to start out with good, clean data, or your analyses could actually do more harm than good.
Whatever data cleaning tools you decide to go with, once your data is ready for analysis there are powerful machine learning AI tools that can put your data to work, so you can make informed decisions to drive your business forward.
MonkeyLearn is a SaaS text analysis platform with a suite of machine learning tools to help you get the most out of your text data – from CRM systems, social media, online reviews, and all over the web.
Sign up to MonkeyLearn to try out powerful text analysis tools on your clean data.
June 1st, 2021