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Warner Bros
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red bull
3m

Services We Offer in Data Cleaning

We ensure our clients get consistent, complete, and robust data to improve the outcomes. Get our data cleansing services focused on cleaning, de-duplicating, verifying, and validating a large pool of erroneous and rogue data.

Data auditing is the foundation of every cleansing engagement we run. We perform a detailed assessment of your current data to ensure its efficacy and quality. Our expert data cleansing team can compile data from large datasets and aggregate it in a more straightforward medium using sum, average, mean, or medium references.

Our end-to-end data verification confirms your records are accurate, consistent and within the tolerance ranges your business rules define. We verify your data at every level, even if it is merged or migrated from an outside source. Our data engineers use manual, semi-automated, and automated methodologies for data verification.

We combine data collected from internal sources with siloed data sources from internal, third-party, and external sources to enrich the value of data in your possession. Our professional data cleansing services empower you to monitor the changes in the quality or sources of data enrichment without compromising data security or compliance.

Our deduplication expertise removes duplicate and redundant records using fuzzy-match, phonetic and rule-based algorithms tuned to your dataset. Our skilled data team performs data deduplication using in-line or background processes, ensuring zero data loss and no downtime.

Our data standardization services help you harmonize data across systems and improve data portability and interoperability. By adhering to the data standards, we transform data collected from numerous sources into a consistent format. These standards cover capitalization, acronyms, punctuation, incorrect value fields, and alpha-numeric characters.

Every dataset is different, so there's no one-size-fits-all approach to data cleaning. Our AI developers tailor data cleansing services to address the specific errors, inconsistencies, and quality issues in your data. Leveraging advanced AI technology and tools, they ensure that your data is thoroughly cleansed and optimized for your needs.

Our data team is highly skilled in managing data health and hygiene. They can monitor and manage your data handling process, from collection to implementation and distribution to data analytics. Providing error-free and consistent data that can serve your intended purpose is the primary aim of our data cleansing services.

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We ensure you’re matched with the right talent based on your requirement.

Tech Stack We Use for Data Cleansing

We use best-in-class tools, state-of-the-art technologies, and modern approaches to scale up your business

Data CleansingIntegrate.ioTibco ClarityDemandToolsRingLeadTrifacta WranglerOpenRefine
Data QualityMelissa Clean SuiteWinPure Clean & MatchInformatica Cloud Data QualityOracle EnterpriseData QualitySAS Data QualityIBM Infosphere Information Server
PM ToolsJiraTrelloSlackAsanaAzure DevOpsHubstaff Tasks
Communication ToolsSlackHangout
MeetingGoogle MeetZoomGoToMeeting

Our Data Cleansing Case Studies

We have completed many data science, BI, and analytics projects. Data cleansing was the central part we executed in many of those projects.

Automotive Insurance Company

Industry: Insurance

Core Technology: CloverDX | ApacheNIFi | MongoDB | Tibco Clarity

The client maintained an in-house server to manage all business data and wanted to move to cloud storage. We helped migrate the entire data infrastructure to the cloud. Post-migration, we performed data cleansing and ensured the client had the right data quality to achieve the intended purpose, resulting in a 35% improvement in data accuracy and a 25% reduction in processing time.

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Manufacturing Facility

Industry: Manufacturing

Core Technology: Tableau | Splunk | SAS Data Quality | Trifacta Wrangler

The client wanted to derive insights from complex machine-generated log data. We used Splunk to collect, index, and analyze the data. Before sending it for analytics, we aggregated, cleansed, enriched, and standardized the data to ensure high-quality inputs for visualization, leading to a 40% faster data processing cycle and a 30% improvement in reporting accuracy.

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A supermarket chain in Australia

Industry: Retail

Core Technology: Power BI | Trifacta Wrangler | IBM Infosphere Information Server

The client came to us requesting detailed insights into their marketing activities. We used Trifacta to cleanse the data and integrate it with BI tools for deeper analysis. The entire process was automated, and KPIs were established to continuously monitor and manage data quality, resulting in a 45% increase in campaign performance visibility, 99% data consistency across sources.

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Our 6-Step Data Cleansing Process

Why Choose Bacancy for Data Cleaning Services?

As a reliable data cleansing service provider, we have gained essential skills and industry expertise to manage and maintain data quality. Our team saves you time and money by providing clean, consistent, and accurate data.

Cleaning your data manually and making it error-free is time-consuming and complicated. But our expertise in utilizing different data cleansing tools and technologies ensures systematic assessment and cleaning of your data in minimum time.

Why Choose Bacancy for Data Cleaning Services?

Advantages of Partnering with us

  • Proven experience handling large-scale structured and unstructured datasets across industries
  • Standardized data cleansing workflows covering deduplication, normalization, validation, and enrichment
  • Strong focus on data accuracy through multi-level quality checks and validation rules
  • Compliance-aligned delivery supporting GDPR, HIPAA, SOC 2, PCI-DSS, and ISO 27001 standards
  • Automated and scalable data processing pipelines for faster turnaround and consistency
  • Flexible engagement models tailored to data volume, complexity, and business needs
  • Signed NDA before data access, ensuring complete confidentiality
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Frequently Asked Questions

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Data wrangling, sometimes called data munging, is the process of reshaping or converting data from one format into another. On the other hand, data cleansing, also called data cleaning, is a process of finding and rectifying errors from a particular dataset.

We also run column-level data profiling and row-level verification (using tools like Informatica Data Quality and OpenRefine) to confirm every record meets your business rules before delivery. We clean the data by removing duplicates, fixing errors, filling in missing values, deleting irrelevant data, and correcting syntax errors.

The cost of our data cleaning services depends on different variables, such as the amount of data, the number of fields, the age of the field, the location of the datasets, and how old it is. Besides, the complexity, methodology, and technology also have a role in determining the costs.

You can contact us with your requirement to get a custom quote.

You will come across different clickable action buttons on the page; click any of them, fill in your requirements, and we will get back to you. Besides, you can fill out the requisition form at the bottom or call us.

The cost of data cleaning services at Bacancy depends on factors such as data volume, complexity, number of data sources, and the level of cleansing required. Simple tasks like deduplication and formatting cost less, while large-scale projects involving multiple systems, enrichment, and automation require more effort.

Flexible engagement models are available, including hourly, fixed cost, and dedicated resource options, so pricing can be aligned with your specific needs. Share your requirements, and a tailored estimate can be provided based on the scope of work.