Oil and Gas Industries have been experiencing market changes, computations and regulatory changes. PIDX comes to the rescue as a global electronic business standard to improve business efficiency by promoting interoperability between IT systems within the oil and gas industry.
We at SoftNis, follow PIDX Standards, Process and Classification Schemas.
PIDX is the American Petroleum Institute's Committee on global electronic business standards in the Oil and Gas Industry. PIDX standards have been extensively adopted across the globe, with Operators, ( large, small, independents and NOCs ) suppliers and third party technology solution providers.
We at Softnis, strongly believe that Data enrichment is a value adding process to provide more information of the product to the customer while enhancing the quality and richness of the product data.
Our Data Enrichment practice follows the methodology of Product sourcing, Identification (Defining Noun Modifiers), Product Classification, Taxonomy Development, Schema Development, Specification capturing, Applications, Features and its Benefits, Information Listing, Description Generation (Long and Short using abbreviations), Inputs from the MSDS (Material Safety Data Sheet) / Technical Data Sheets / Installation Sheets, and Image Capture / Format / Resizing.
Resources would include manufacturers / Supplier’s website, datasheets, and indexes, catalogues and other relevant documents
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A meticulous process of rearranging Data to a Suitable Form as per Customer Specifications after analyzing the given Input Product Description. For example, in Supply Chain Management usually suppliers cannot use the data in the manufacturer's website directly. The product data has to be cleansed to suit individual customer requirements.
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We are specialized in UNSPSC, eCl@ss and Custom Classification and have worked on data in more than 5 languages, mainly English, Spanish, German, French and Italian.
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This is process of finding the same item in the competitor website and capturing the price for reference.
Duplicates are identified and eliminated by adopting various permutations of pattern matching rules, database queries and manual inspection.
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