Asset inventory. Evolved.
An Asset Inventory – much like business glossaries and data dictionaries – are core components of modern data management, which is essential for defining a register of technical assets.
Due to the volume, complexity and rapidly evolving nature of the technology landscape, many organisations are unable to maintain a consistent comprehension of their digital estates.
Systems, mainframes, databases, interfaces, queues, topics, servers and virtual machines are only a few of the thousands of types of both physical and logical assets that an organisation may have acquired over time.
Solidatus is designed to make all aspects of data management faster by enabling organisations to quickly and easily discover, curate and catalog data at truly enterprise scale.
Not only do organisations need to understand the what, but they also need to understand the why and the who, both in terms of ownership as well as use. An accurate and complete asset inventory enables the organisation to perform analytics that minimises duplication, redundancy, risks and costs.
A modern Asset Inventory should enable centralised control with a collaborative, federated model for initially identifying, documenting and classifying assets. A well curated inventory can then be used to plan, assess and implement technology change across an organisation.
Solidatus is the next generation, industry-leading, Asset Inventory
Solidatus Asset Inventories are fully integrated, feature-rich, meticulously designed and machine learning (ML) assisted. Designed to help organisations rapidly identify, document and share their physical and logical data assets, their most valuable resources. Solidatus enables asset inventories to be tagged and linked seamlessly with data lineage models and business glossaries creating a complete end-to-end map of all data held along with its interaction with purpose and retention.
Organisational impacts of an asset inventory used in conjunction with data lineage are far more significant than when used in isolation. The Solidatus Asset Inventory provides the technical what is, while the lineage helps provide the where, who and why, the context that gives meaning and value to metadata.
The Solidatus Asset Inventory is the next evolutionary step. Solidatus listens and has learned from those asset inventories that have come before. Taking the most useful and requested features and integrating them into an operational framework. Utilising Solidatus’ simple, flexible, extendable UI/UX and our unique temporal/bi-temporal, versioned property graph technology to bring a new level of power and control to organisations.
The advanced rules engine and graph analytics enable organisations to analyse and define rules ensuring both structural integrity of the data containers, and the processes that interact with them. Whether to find data assets, identify data quality issues, or manage other data management and compliance problems, Solidatus puts the power into every user’s hands.
Asset Inventories help organisations to catalog and manage their ever-increasing volume and diversity of technology assets more effectively, while avoiding legacy risk.
Collaborative knowledge-sharing helps organisations break down silos, gaining better insights into data ecosystems, identifying redundancies, streamlining processes and reducing costs.
Systematic identification of the sources of poor-quality data reduces business risk, highlighting where potential issues can arise. Data asset planning allows organisations to future-proof, by maintaining a constant assessment of accumulating technical debt.
Businesses can enrich their data assets’ physical attributes with business metadata to increase data understanding and insight to help drive their business intelligence.
Complete and well curated Asset Inventories support organisations in their efforts to reduce the burden of regulations by providing demonstrable control and operational transparency.
Solidatus’ unique crowdsourcing, automated importing and heuristic matching engine, enables an organisation to quickly and effectively gather and model organisational data.