Data cleaning stories

Fintech integrators turn to Melissa's real-time, trusted data layer to sharpen KYB checks, slash onboarding friction and cut synthetic fraud.

Learn simple and scalable ways to check if a phone number is active, improve data accuracy and keep your customer communications on track.

Insurers race to clean and connect sprawling customer records into a single AI‑ready view, paving the way for hyper‑personalised cover.

Enterprises must replace ad-hoc data cleansing with real-time, AI-ready data integrity architecture to secure compliance and competitive edge.

Sales teams waste time on dead numbers; verified phone data turns outreach into real conversations, better leads and higher conversions.

Chartered accountants warn of widening AI skills gap as vast majority seek urgent, hands-on training to use new tools safely and effectively.

SaaS vendors are baking real-time data quality checks into core products to cut waste, curb fraud, and turn cleaner data into trust.

In 2026, retailers win not by owning more data, but by orchestrating trusted, real-time data that powers every decision and experience.

Melissa's global phone verification delivers real-time accuracy, fraud protection and compliance, turning unreliable phone data into growth.

Duplicate patient records can jeopardise safety, inflate costs and risk fines; here's how better data practices and tools can prevent them.

As data grows messy and massive, AI-powered matching promises sharper insight, lower long-run costs and an edge over rigid rule-based tools.

Clean B2B data boosts marketing, sales and compliance; profiling, validating and standardising records cuts waste and sharpens decisions.

Outdated, inaccurate and duplicate records are crippling data-driven decisions, but simple verification and cleansing tools can reverse the damage.

Digital transformation falters not for lack of tech, but because untrusted data quietly undermines scale, speed and customer experience.

Generative AI promises transformation, but without modern, rigorous data governance frameworks, projects risk failure, fines and lost trust.

Bad data is quietly wrecking Asia's eCommerce, fuelling failed deliveries, higher costs and eroding customer trust from click to doorstep.

Flawed, fragmented data is wasting time, money and AI potential; firms must fix ownership, visibility and tooling to restore trust.

Dirty B2B data silently drains revenue; smart cleansing, automation and best practice can revive performance and protect your brand.

Phone numbers are becoming the new trust filter, helping businesses block fraud, cut wasted messages and secure real, reachable customers.

Tamr launches Curator Hub, combining AI and human oversight to improve complex data quality and support enterprises' generative AI projects.