5 Advantages of Data Cleansing
Data cleansing is the process of spotting and rectifying inaccurate or corrupt data from a database. The process is mainly used in databases were incorrect, incomplete, inaccurate or irrelevant part of the data is identified and then modified, replaced or deleted.
A data-driven marketing survey conducted by Tetra data found that 40% of marketers found that various departments in a business enterprise do not use data effectively. Managing and ensuring that the data is clean can provide significant business value. Business enterprises can avoid a lot of hassles such as the high cost involved in processing errors, manual troubleshooting, incorrect invoice data and shipments to the wrong address by cleansing their data. The information of the customer is forever changing due to relocation or other factors which must be changed, and the updated information must reflect in the database. Business enterprises can achieve a wide range of benefits by cleansing data which can lead to lowering operational costs and maximizing profits.
Here are the advantages of data cleansing:
- Improves the Efficiency
- Improves Decision Making Process
- Streamlines Business Practices
- Increases Productivity
- Increases Revenue
Reliable Inc. will access your end-to-end data infrastructure, virtually integrate multi-source data sets, clean and synchronize. Our techniques will address both structured and unstructured data assets. We build custom tools and utilities, as and when needed.
Data cleaning services include the process of detecting and correcting errors and inconsistencies from a data set in order to improve its quality. Our data cleaning services aim not just to clean the data, but also to bring uniformity to different data sets that have been merged from other sources. After cleansing, a data set should be consistent with similar data sets within the system. We provide a full suite of data cleansing services
- Import Data: Unclean data from your systems (structured and unstructured) is imported into our cleansing system. Typically provided by you in ASCII database extract, Excel, CSV, or Tab-Separated Text file format.
- Merge Data Sets: Data from multiple differently formatted sources (databases, applications, excel, csv, sql, sap, etc) is converted and merged into a common database.
- Rebuild Missing Data: Wherever possible, missing information is recreated (e.g. well name, current status, etc.).
- Standardize Data: Data is combined, separated or modified to ensure that the same standards are applied across data from each source. This step ensures the creation of a standardized dataset that can be used to populate the master data source.
- Normalise Data: Similar data is normalised (e.g. uwi, well name, well status, etc).
- De-Duplicate data: We use a custom-built fuzzy-matching algorithm to identify potential duplicates. Our methodology provides high accuracy matches with a tolerance for misspelling, missing values or different values. For mission-critical data, these results are manually reviewed (by either us or our client) and the database updated accordingly.
- Verify & Enrich Data: Data is validated against internal and external database sources and additional value-adding info is appended. Alternatively, we also provide self-verification services.
- Export Data: Data can be exported in numerous formats, for example, excel, csv, SQL database, XML, tiff, PDF, or as required. Typically, we return it in the same layout and format that we receive it.