Hey linkedln fam👋 Let us understand the concept of Reference Data Management. Have you ever thought how businesses keeps their accuracy and consistency in their data, here enters the RDM which ensures the data management and helps in decision making. What is RDM? RDM involves the management of transactional data used to categorize the transaction and provides analytical insights. It gathers wide range of data types such as security identifier, country codes etc. 🔎The process of RDM 1) Collection - Identify the types of reference data and gather reference data from internal and external sources. 2) Consolidation - The data is being consolidated and then and provide it into common model and compile it. 3) Cleansing - Here the data is being clean and the unnecessary data is being removed from the data set. 4) Coordination - Here the data is being manually check so as to avoid the exceptional error. 5) Distribution- At this stage the data is distributed internally and externally to the relevant concerned person. Examples - Security identifier It's the unique code which is assigned to the financial instrument such as stocks and bonds. For instance, ISIN (International security identification number) the ISIN for LIC is INE0J1Y01017 this is unique identifier code for securities worldwide which ensures efficient trading and reporting. RDM plays a major role in ensuring the security identifier and other reference data are accurate, consistent, and up to date which facilitates the operations and reducing risks. #Datamanagement #Refrencedata #RDM #Imarticus #investmentbank #bnymellon #jpmorgan
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'Many of the capital markets firms participating in the study are still using decades-old methods including email and FTP file transfers to share data in bulk, typically once a day at close of trading.' = adding signifiant cost + risk to the process around capturing the data required to support daily activities, in an increasingly data-centric world. 'At large firms, 83% of respondents believe extract, transfer and load (ETL) solutions are challenging due to growing volumes of data, complicating efficiency and increasing the risk of errors. " = these are way too expensive, complex and slow to make changes to, forcing users to revert to alternative mechanisms (email + "human api's") to get data safely from a to b. At Duco we bring you the power to solve these problems quickly, easily and efficiently. And enable you to future proof your business. #dataautomation #capitalmarkets #posttrade https://lnkd.in/eJwbWpK7
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What is RDM ? RDM ( Reference Data Management) is the term where data will be stored seamlessly, to maintain the static financial data store. such as securities,legal entity identifiers, maturity dates and customer data , transactions etc. It helps to ensure the process is reliable or not to the business. Process of RDM- 1) Collection 2) consolidation 3) cleaning 4) Coordination 5) Distribution/Execution An International Securities Identification Number (ISIN) is a code that uniquely identifies a security globally for the purposes of facilitating clearing, reporting and settlement of trades. It consists of a 12-character alphanumeric code that uniquely identifies a security and helps to facilitate trading and settlement processes. They consist of both letters and numbers. These include the country in which the issuing company is headquartered (first two digits), along with a number specific to the security (middle nine digits), and a final character Number is used as Check for example it will be 0,1...,.9. Example - INE040A01026 #investmentbanking,#imarticuslearning,#sql,#referencedatamanagement
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Data is one of the most valuable assets a business can have. 𝗗𝗮𝘁𝗮 𝗹𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 (DLM) governs the handling, storage, and disposal of data: effective DLM is crucial for data security and operational efficiency. How to Navigate the Challenges of Data Lifecycle Management: 𝟭. Your DLM strategy must account for structured and unstructured data. 𝟮. Secure data in all stages: transmission, storage, deletion, etc. 𝟯. Put data quality controls in place to ensure integrity. 𝟰. Define data retention and deletion timeframes. I go into further detail in my blog; https://lnkd.in/eHxkZTpb
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Navigating the Challenges of Data Lifecycle Management Data is one of the most valuable assets a business can have. Managing this data throughout its lifecycle can be challenging. Data lifecycle management (DLM) refers to several processes and policies. They govern the handling, storage, and eventual disposal of data.Businesses generate and store vast amounts of data. As this Read more: https://lnkd.in/grFE5VN2 #ITservices #ITstrategy #ITmanagement #technology
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Three Pillars of UEBA Gartner’s definition includes three primary attributes of UEBA systems: Use cases—UEBA solutions report the behavior of entities and users in a network. It detects, monitoring and alerting of anomalies. UEBA solutions need to be relevant for multiple use cases, unlike systems that perform specialized analysis such as trusted host monitoring, fraud detection, etc. Data sources—UEBA solutions can ingest data from a general data repository. Such repositories include data warehouse, data lake or Security Information and Event Management (SIEM). UEBA tools don’t place software agents directly in the IT environment to collect the data. Analytics—UEBA solutions isolate anomalies using analytic methods, including machine learning, statistical models, rules and threat signatures.
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🚀 Accelerate Your Data Compliance with Orion Governance's EIIG! 🚀 Struggling with data compliance? 🌐 Meet the Enterprise Information Intelligence Graph (EIIG) by Orion Governance – your ultimate solution for streamlined compliance! 🔍 Why EIIG? - Automated detailed data lineage for accurate traceability - Real-time quality assessment and monitoring - Comprehensive support for 70+ technologies Say goodbye to manual efforts and hello to efficiency and accuracy! Ensure your data meets regulatory standards effortlessly. Ready to take control of your data compliance? Let EIIG lead the way! 💪 Download our free case study on how EIIG helps enterprises accelerate data governance: [link to case study] #DataCompliance #DataGovernance #OrionGovernance #EIIG #DataFabric #DataLineage
Success Story: Enterprise Accelerates Data Governance with Orion Governance
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As someone assigned to documentation for almost my entire corporate life, these tips on data lifecycle management are very helpful.
Data is one of the most valuable assets a business can have. Managing this data throughout its lifecycle can be challenging. Data lifecycle management (DLM) governs the handling, storage, and disposal of data. Effective DLM is crucial for data security and operational efficiency. 𝗛𝗼𝘄 𝘁𝗼 𝗡𝗮𝘃𝗶𝗴𝗮𝘁𝗲 𝘁𝗵𝗲 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗼𝗳 𝗗𝗮𝘁𝗮 𝗟𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 ✅ Your DLM strategy must account for both structured and unstructured data. ✅ Secure data in all stages: transmission, storage, deletion, etc. ✅ Put data quality controls in place to ensure integrity. ✅ Define data retention and deletion timeframes. Reach out to us today for help with DLM solutions. https://lnkd.in/esF3XQ9f
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Data is one of the most valuable assets a business can have. Managing this data throughout its lifecycle can be challenging. Data lifecycle management (DLM) governs the handling, storage, and disposal of data. Effective DLM is crucial for data security and operational efficiency. 𝗛𝗼𝘄 𝘁𝗼 𝗡𝗮𝘃𝗶𝗴𝗮𝘁𝗲 𝘁𝗵𝗲 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗼𝗳 𝗗𝗮𝘁𝗮 𝗟𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 ✅ Your DLM strategy must account for both structured and unstructured data. ✅ Secure data in all stages: transmission, storage, deletion, etc. ✅ Put data quality controls in place to ensure integrity. ✅ Define data retention and deletion timeframes. Reach out to us today for help with DLM solutions. https://lnkd.in/esF3XQ9f
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For wealth managers to benefit fully from self-service analytics, they need a simplified data management solution that seamlessly integrates with the systems they use. This is where the LXA analytics platform comes in. It allows users to easily build a wide range of use cases across the wealth management life cycle and is pre-integrated into popular vendor platforms such as Avaloq. Learn more: https://lnkd.in/g3g4SQyj #Banking #WealthManagement #DataAnalytics
LXA analytics helps wealth managers optimize portfolios and reduce risk | Luxoft
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🔍 The Importance of Data Quality in Decision-Making In today’s fast-paced world, the quality of your data is more crucial than ever. Using inaccurate or incomplete data can lead to poor decisions, affecting not just individual outcomes but entire organizations. This is why we at WSD/SPi invest significant time and effort into ensuring our data coverage is impeccable. 1️⃣ Time Investment in Data Coverage We spend countless hours refining our processes to ensure that our data coverage is as comprehensive and accurate as possible. Perfect coverage isn’t just a goal—it’s a necessity. 2️⃣ Rigorous Data Validation Data quality isn’t just about collecting information; it’s about verifying it. We employ both automated and human validation processes to catch and correct errors before they impact our clients. This meticulous attention to detail sets us apart. 3️⃣ Continuous Improvement Through Feedback We believe that data quality is a journey, not a destination. That’s why we constantly seek feedback from our clients and partners. Every day, we’re on the lookout for errors and new ways to enhance our data, ensuring that it meets the highest standards. This dedication to data quality is why Structured Products Intelligence | SPi boasts the best #structuredproducts database in the industry. To make it evident, here’s the correct volume for the US market in H1 2024 (by issue date): 📊 Registered Notes - $81.3 billion (100% coverage) 📊 Unregistered Notes - $8.4 billion (we estimate this represents 80% of the total market) 📊 MLCDs - $1.4 billion (we estimate this represents 50% of the total market) Accurate data is the foundation of sound decisions. Let's keep striving for excellence! 💪 #DataQuality #DataValidation #ContinuousImprovement
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