Many Options to Help Clean Up Your Data

For organizations looking to make sense of their data, the first step is to ensure the data are managed well – are consistent, accurate and that rules are in force to keep users from doing anything to undermine data integrity. But whether you’re trying to ensure data quality going forward or clean up a whole history of sloppy data, the choices in the marketplace can be bewildering.

Market research firm Gartner reports businesses and governments invested $1.4 billion in data quality tools in 2014. It projects the market will top $2.1 billion by 2017 and breaks down the types of tools into eight categories:

  • Generalized cleansing. Modification of data values to meet domain restrictions, integrity constraints or other business rules
  • Data profiling and data quality measurement. Analysis to capture metadata that can help to identify data quality issues
  • Parsing and standardization. Decomposing text fields into component parts and formatting values into consistent layouts
  • Matching. Identifying, linking or merging related entries within or across datasets
  • Monitoring. Imposing controls to ensure data conforms to business rules that define data quality for an organization
  • Issue resolution and workflow. Identifying, quarantining and resolving data quality issues using processes and interfaces that enable collaboration with key roles, such as data stewards
  • Enrichment. Enhancing the value of internally held data by appending related attributes from external sources (such as mapping or location data)

Dirty Data Got You Down? Clean it Up

Harnessing government data to make better decisions is a great concept – but most databases require significant cleanup before they can start pointing decision-makers to smarter results.

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Gartner identifies 18 vendors in its “Magic Quadrant” report for data quality tools, a list that includes both major database software leaders like SAP, Oracle and IBM, along with other specialists. The leading specialists, according to Gartner:

  • Informatica. The company’s products are seen as among the easiest for both technical and non-technical users to navigate
  • Information Builders. The tools locate and rectify bad data – and also proactively stop bad data from entering the environment
  • Talend. Its tools profile, cleanse and mask data, using validation, standardization and enrichment techniques, along with integrated parsing technology to standardize and de-duplicate unstructured data
  • Trillium. These products emphasize data governance structures, strategies, practices and policies and include tools to put those in place, the company says
  • Neoppost. Validation and standardization products ensure clean data capture, including de-duplication and ensuring new data is relevant when integrating with existing data sets, the company says
  • Ataccama. The company offers industry-specific solutions including government products addressing such areas as tax compliance, Security and Law Enforcement, government information sharing requirements and interagency collaboration
  • MIOsoft. Tools embrace master data management, data migration and information governance initiatives using a virtual “lens” over data, so that original data and systems are untouched

1 Comment

  1. Outsource Data Entry

    Ensuring quality of data is very important for a business and it can be gained through accurate data cleansing services. Data cleansing will ensure consistency of data.

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