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The need for data enrichment services
What are the benefits of data enrichment services
The data enrichment process uncovered
What Makes Enrichment with Sharecat Data Services Different?
The value of verified “manufacturer”, “part number”, and “model number” fields in ERP and CMMS systems
Are you ready to transform your data?FAQs - Data Enrichment
FAQs - Data Enrichment
Reliable, straight forward data cleansing services from a proven specialist
Cleansing And Cleaning a Wide Range of Data
How We Do It: The Sharecat Data Cleansing and Formatting Process
Low-Quality Data is a Problem You Can't Afford
Gain a Competitive Advantage With Our Data Cleansing Solutions
Why Pick Sharecat for Data Cleansing
FAQs - Data Cleansing
Data cataloging vs data entry
Reliable data cataloging results in accurate data
What are the benefits of using a data cataloging service?
Data Cataloging: The Sharecat approach
Gain the advantage with data cataloging
Are you ready to transform your data?
FAQs - Data Cataloging
You can't have great data without data standardisation
Data standardiastion is not "one size fits all"
Sharecat actively participates in various initiatives for complex and heavy industries
The Sharecat Data Standardisation Process
Our services help you overcome Data Standardisation Challenges
Benefits of Successful Data Standardisation
FAQs - Data Standardisation
Standardising and aligning your data structure, definitions, requirements, and descriptions prevents inconsistent data and the barriers, bottlenecks and restrictions in processes that typically result.
Data standardisation is fundamental for any organisation wishing to evolve and improve through digitalization. Defining consistent formats and predefined rules across your organisation is the basis for further processing, analysis and use of your data.
Without data standardisation, you cannot;
· Identify when data is correct and reliable or not, which means you cannot trust the output from your ERP and CMMS systems.
· Normalise or harmonise data to be consistent, as you do not have a structure to apply
· Effectively cleanse, enrich and improve data to be more valuable
· Process and deliver new data efficiently to build a reliable source of master data
· Implement new systems and migrate data efficiently between systems
· Integrate systems to use a common source of reliable data
· Use automation to reduce high-volume, low-value data processes.
· Have strong data governance processes
How you standardise your data depends on who you are as a company, which industry you operate in, what systems you use and what regulatory requirements you must meet – all of which are elements that change over time. This is why specialist services in data standardisation make a major impact on your operations, no matter the size of your business.
Get in touch, and our subject matter experts can guide you on the best data standardisation approach for your operations.
Item 1
Item 2
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Emerson Fisher
Fisher
Fisher C
Fisher Controls
Fisher Controls
Fisher Controls
Manufactuer
Caterpliar
Caterpillar
Manufactuer
Part Number
Rosemount
305ITG3A2B21KE7M6T1P8Q4Q8C4C5
Fisher Controls
3051TG3A2B21KE7M6T1P8Q4Q8C4C5
Defining, applying and maintaining your data standards and structure requires knowledge and understanding of the practices, industry initiatives, system requirements and regulatory landscape, which can only be provided by data structuring services from a specialist who understands your business and industry in context.
This is why Sharecat data standardisation is specialized in helping operators in heavy and complex industries such as oil, gas & LNG, chemical and process, utilities and pharmaceutical.
Standardising formats for fields such as dates, currencies and language is only one area of Sharecat’s data standardisation services. For ERP and CMMS systems, equipment and parts data are critical for master data management and require more comprehensive standardisation structures due to the complex data sets and relationships.
Reference Data Libraries (RDL), also known as Class Libraries, are a core element of our data standardisation services as they establish and enforce a structured classification system (taxonomy). They help you have consistency in terms, definitions, formats and relationships for the data required for your facilities, equipment and parts.
Reference Data Libraries can also help you clearly define and communicate your data requirements. Both internally and to your supply chain and engineering contractors, improving compliance and handover, and setting the stage for effective Data Cleansing, Data Enrichment and Data Cataloguing.
Reference data libraries define the categories, hierarchies, input fields and relationships between
· Types of equipment
· Types of documentation
· Associated data and metadata fields such as;
o Equipment properties & attributes
o Design / functional properties & attributes
o Units of measure
o Contents and type codes
o File formats
Using reference data libraries results in a clear framework for classification and consistent categorisation that aligns with standards and initiatives that are applicable to your operations.
This prevents inconsistencies and errors by restricting the entry of data to predefined functional and equipment classes, document types, units of measure and legal values or picklists that accurately reflect the industry and company-specific context of your business.
As part of our data standardisation services, we can help you establish, update and/or maintain a reference data library that sets a clear structure for your data needs in your ERP and CMMS systems. Including recommending relevant best practices, industry initiatives and standards to align with, where relevant, for your company and operations.
Data standard mapping services align and interpret the terms, definitions, relationships and hierarchies between different reference data libraries, industry initiatives and standards. This enables translating different data sets into a common format and transforming data into a new structure.
Many companies with international operations require to use a range of standards and reference data libraries due to regional requirements and differences. Sharecat Data Services subject matter experts can help map between relevant standards as part of a data standardisation service to make it possible to use different data standards in different parts of your business without suffering from silos.
Sharecat doesn't only provide data standardisation and related services. We actively shape the future of data processes and standards by proudly participating in a range of industry groups and initiatives.
Our involvement ensures we're always up to speed on industry developments so the clients can benefit from the latest data standardisation trends and practices. When you work with Sharecat, you can be confident that your data is aligned with the highest industry standards, both now and in the future.
The CFIHOS (Capital Facilities Information Handover Specification – JIP 36) and JIP 33 (Joint Industry Programme 33) groups led by IOGP, where we contribute to defining and refining the standards that govern data management practices being used in the global energy industry.
The Digital Data Chain Consortium, where Sharecat is a member, is focused on improvements for equipment and parts information for the chemical, process and pharmaceutical industries. Aligning on the use of standards such as ISO 61406, VDI 2770 and the Asset Administration Shell concept from the IDTA.
DEXPI aims to develop a common data exchange standard for the process industry, covering all phases of the asset lifecycle, from design project execution and into operations.
Sharecat supports EqHub, which is an industry initiative in Norway led by Offshore Norge to support and simplify information and documentation delivery processes for Norwegian oil and gas using the READI-TIRC and NORSOK industry standards.
Our process for data Standardisation sets the order for your data, creating a unified approach across your organisation. Using the following steps, we establish the standardisation approach specific to your company, applying relevant and required industry standards to meet your specific operational needs:
Our team profiles and assesses your current data, standards and structures, including:
· Analysing the existing data across all silos and systems as relevant
· Identifying patterns and anomalies
· Detecting quality issues
Our analysis identifies variations, inconsistencies, and structural issues caused by a lack of clear definitions and standardisation. This gives us the insight to identify the weaknesses, guiding the next steps to establish the standardisation approach tailored for your unique data environment.
Once we understand the specific data challenges you have, we recommend the most suitable data classification and standardisation system for your needs. We align your data with standards such as CFIHOS, eClass, ISO, or create a hybrid system as best suited for the sector or industry you operate within. Our recommendations also match your geographic location, ensuring your data adheres to both global and local standards.
Our recommendations consider a range of industry best practices and standards as fit best for your company which are tailored to your industry and location. These often include:
CFIHOS (Capital Facilities Information Handover Specification): Ensuring data consistency and integrity in capital projects within the energy sector.
eClass: A classification system for products and services that standardises data across industries, especially in product descriptions.
IEC standards: Such as IEC CDD, IEC 61355 and IEC 60050, which provide comprehensive definitions for electrotechnical equipment, products and terminology.
ISO 15926: A standard for the lifecycle data of process plants, ensuring interoperability and data exchange between computer systems.
NORSOK: Standards used in the Norwegian petroleum industry to ensure consistent data management, safety, and cost-effectiveness.
PIDX: standard for efficient eBusiness in the Global Oil and Gas industry
POSC Caesar: standard technical information and structured information models for the oil and gas industry and other heavy asset industries.
READI TIRC: A data standard focused on real-time information and technical requirements and classification.
UNSPSC: A UN standard for product and service classification, enabling efficient procurement and spend analysis.
Asset Administration Shell & its Sub-models: A standard framework for representing digital twins of assets, standardizing relevant data and services for sharing information.
VDI 2770: A guideline for the digitalisation of technical documentation developed by the Association of German Engineers (VDI - Verein Deutscher Ingenieure).
Having identified the current weaknesses and recommended the approach and standards to apply, the next step is for our data standardisation experts to create your company-specific reference data library.
Our team drafts the reference data library in a collaborative process with your team so that, once finalized, your team is familiar with and ready to take ownership of the reference data library to begin implementation and use.
It’s important to highlight that even though a reference data library may be aligned or based on an international standard or industry initiative, it must also be unique to your company and operations to give the best value.
Once we have defined and established the data Standardisation approach for your business, the next step is to implement it in your systems and operations. This can be through a combination of Data Cleansing, Data Enrichment and Data Cataloguing, to harmonize and normalize your data by applying the necessary formatting, categorization, and structure.
Our services for data Standardisation can continue after the delivery of your reference data library with ongoing support, maintenance and updates to keep your data standards aligned with evolving industry standards, regulatory requirements and business needs.
Organisations often face challenges that can make data standardisation time-consuming and difficult to achieve. At Sharecat, we know these challenges and work closely with our clients to help make the standardisation journey smooth, predictable, and cost-effective. Some of the typical challenges we help customers address are:
Resistance to change is a common barrier to data standardisation. The transition to a standardised approach can be met with reluctance due to variations that often arise from departmental terminologies or influences from external data providers.
This is why it is important to use an expert service for data standardisation that can bring control of the varying definitions, take account of them in a new structure, and help align teams to the benefit of a new common approach.
Many organisations rely on legacy systems that are often outdated and don't follow modern standardisation practices. These systems don't follow up-to-date standardisation approaches and methods, making it difficult to apply uniform data standards across the organisation. This is a common challenge and one that requires careful consideration in the data standardisation process as to how the restrictions of legacy systems can be addressed while achieving a consistent data standard.
Migrating data from legacy ERP and CMMS software to modern platforms often involves complex technical challenges and significant resource investment, as well as the risk of data loss or corruption during the transition. To successfully migrate your data, it is critical to have prepared the mapping from the legacy data structure to the new data structure. This requires a clear understanding of the as-is data structure in the legacy system and defining a new data structure for the new system. Without data standardisation preparation, any migration will struggle and often fail.
Implementing data standardisation requires significant resources, including time, personnel with a unique understanding, and financial investment. Organisations often face constraints in one or more of these areas, making it challenging to allocate the necessary resources. The process can be particularly difficult for small to medium-sized enterprises (SMEs) with limited budgets and staff. Our data standardisation services enable companies to benefit from an expert partner to improve standardisation faster, at a lower cost, and with a better result than if you did it yourself.
Achieving data standardisation ultimately sets the foundation for more efficient and effective master data management and creating strength in your data. This is through a range of individual benefits:
Standardisation ensures data accuracy, reliability, and consistency across all systems and processes.
ERP and CMMS systems have considerable automated capabilities that can save costs, but only if the data is consistent and reliable. For example, standardising short text and long text generation enables automated ordering from ERP systems.
A cleaner dataset means simpler data governance processes and lower maintenance required to keep your data quality and strength high while also reducing the need for future data cleansing.
Implementing new data systems can be expensive, disruptive and difficult if the data being inputted and used is unstructured and of poor quality.
With a standardised structure, further data processing to improve your existing data’s value and usefulness, including Data Cleansing, Data Enrichment and Data Cataloguing, becomes more efficient and cheaper.
Standardised data is easier to integrate across different systems, enhancing interoperability and enabling seamless data sharing.
A common standardised approach enables operators to create a unified data environment where every item is placed correctly according to a predefined hierarchy and set of categories, further streamlining the flow and use of information in your ERP and CMMS systems.
Adopting a uniform, standardised approach to your data will increase the data’s accuracy and comparative basis between datasets, which improves the quality of data analysis. Improved understanding of the datasets means more precise and reliable insights to improve decision-making and strategic planning.
Data Standardisation, when done correctly, aligns the data structure to relevant company processes and regulations, which is a core part of effective data governance. A strong data standardisation foundation reduces the risk of data breaches, legal penalties, and reputational damage.
Get in Touch Today
If you are ready for a dedicated, expert approached to data standardisation, tailored to deliver real improvements for your operations, then please
If you’re ready, we’d love to talk to you to find out if Sharecat Data Services is the right partner to help remove restrictions and unlock value through making your data more reliable and accurate.
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