Product Data Solutions
Product Data Solutions involves organizing, structuring, storing, and tracking the product information created by the product design team as they carry out engineering and development activities, controls all product-related data and associated workflow processes within an enterprise.
Product Data and process-related information in a single, central system. This information includes effective data, models, parts information, manufacturing instructions, requirements, notes and documents. The ideal PDM system is accessible by multiple applications and multiple teams across an organization, and supports business-specific needs.
- Time-to-Market
- Improved Productivity
- Improved Control
- Find the correct data quickly
- Improve productivity and reduce cycle times
- Reduce development errors and costs
- Improve value chain orchestration
- Meet business and regulatory requirements
- Optimize operational resources
- Facilitate collaboration between global teams
Provide visibility for better business decision-making
Data Cleansing
Data cleaning is the process of preparing data for analysis by removing or modifying data that is incorrect, incomplete, irrelevant, duplicated, or improperly formatted. This data is usually not necessary or helpful when it comes to analyzing data because it may hinder the process or provide inaccurate results.
Data Mining
Data mining is a very popular topic nowadays. Unlike a few years ago, everything is bind with data now and we are capable of handling these kinds of large data well.
By collecting and inspecting these data, people were able to discover some patterns. Even the whole data set is a junk, there are some hidden patterns that can be extracted by combining multiple data sources to provide valuable insights.
Data mining is often combined with various sources of data including enterprise data that is secured by an organization and has privacy issues and sometimes multiple sources are integrated including third party data, customer demographics and financial data etc.
Data Standardization
Standardized product data also conveys a considerable long-term advantage for online retailers, in the sense that it recovers their competence in building, importing, and managing the product data, ensuring a higher level of consistency and data quality. Though, most eCommerce stores distrust the data available in their systems as they face serious problems with the quality of product data.
Data Normalization
Normalization is a process used to organize a database into tables and columns. The main idea with this is that a table should be about a specific topic and only supporting topics included. Take a spreadsheet containing the information as an example, where the data contains salespeople and customers serving several purposes:
Identify salespeople in your organization
List all customers your company calls upon to sell a product
Identify which salespeople call on specific customers.
By limiting a table to one purpose you reduce the number of duplicate data contained within your database. This eliminates some issues stemming from database modifications.
Attribute Data Extraction
Standardized product data also conveys a considerable long-term advantage for online retailers, in the sense that it recovers their competence in building, importing, and managing the product data, ensuring a higher level of consistency and data quality. Though, most eCommerce stores distrust the data available in their systems as they face serious problems with the quality of product data.