Semantic Web – Page 3 – Blue River Systems Group, LLC

18 Aug

Explicit Connections over Implicit Relationships

in HTAP

Low-friction data structures are those that: 1) are self-describing, 2) directly represent that which they model, and 3) do not require transformation between operations and analytics. Our graph-throughout approach to Hybrid Transactional / Analytic Processing system development encourages a direct connection between business and IT where data model creation can be collaborative.

Once the discrete, well-bounded RDF data model is designed, the backend system is generated, ready for: 1) behavioral augmentation where necessary, 2) test, and 3) deploy. Monolith and command-and-control are out, well-bounded microservice, distributed, and peer-to-peer are in.

This low-code approach helps to address the: 1) human resource impact of adopting new technology, 2) communication overhead of translating business concerns to production enterprise software, 3) adaptability of systems to business need, and 4) explicit connection between operational and analytic systems.

In contrast to relational and columnar data management which rely on implicit relationships embedded in SQL, Temporal Linked Data® (TLD) makes an explicit connection between temporal data aggregates.

Likewise, where Event Stores keep all data domain events together, TLD keeps all temporal data alongside the aggregate to which it belongs.

Explicit connections are both hard and soft, technical and social. Hybrid Transactional / Analytic Processing by way of TLD explicitly connects:

Temporal data aggregates,
Operational data with analytic data for realtime analysis,
Business and IT personnel, and
Represents the shortest path between business concept and production deployment.

Amundsen Scott South Pole Station, a low-friction location to view the night sky (NSF Public Domain Image)

21 Jul

Full Spectrum Analytic Use Cases—No Special Cases

by Alan Strait

in HTAP

Comments

The fact that a chosen analytics platform does not span the entire analytic use case spectrum can be cause for concern and reevaluation. The temptation is to reach for a niche, special case platform or solution, but this may eliminate valuable and desirable forces.

Special case efforts tend to result in one-off projects rather than being available for the ordinary course of business. This tends to reduce the expectation of timeliness and scaleability. It can also unduly limit valuable concepts and algorithms by believing they cannot be used generally.

Page Rank is a good example of an algorithm that has general applicability as a measure of influence in a community, but that can be left out because the current analytic platform does not handle it well.

Full Spectrum Solution

Our own commitment to a graph-throughout architecture with realtime data projection to a third-generation graph analytics platform provides the best chance of being able to use the right algorithm for the job, whether realtime analysis, historical analysis, creating machine learning data sets, or applying explainable AI (as provided by TigerGraph), as well as more RDF-oriented Knowledge Graph solutions (such as our friends at ReactiveCore provide).

The time for graph-based transactional and analytic solutions is here. Please do have a read through our weblogs discussing Hybrid Transactional / Analytic Processing by way of Temporal Linked Data®.

BRSG advocates for business-oriented goals as well as considering lost forces that inhibit the ability to serve The Business well. Please reach out if we can be of service: info@brsg.io, or call 303.309.6240.

14 Jul

Holistic HTAP, in Service to The Business

by Alan Strait

in HTAP, Semantic Web

Comments

In a prior post, enterprise data was compared with an “hydraulic data cycle” where analytics would rain insight from precipitation drawn across “all” operational environments. Rather than analytics being an afterthought, HTAP raises “business guidance” through analytics to first class citizen along side operational systems with realtime, temporal data projections.

Information Technology should view itself as part of and critical to the success of the businesses that it serves by regularly identifying, prioritizing, and delivering on the needs of The Business as enabled by: 1) collaborative and agile processes, and 2) scalable and reliable microservice deployments by way of container orchestration to hybrid on-premise, virtual-private, and public cloud platforms.

Detail in the Big Picture

The resulting fine grained transactional deployments have to be reconciled against the need for a realtime 360 degree view of current and historic data for analytics and business guidance.

In like fashion, Blue River Systems Group advocates for high-throughput, low-latency, scale-out transactional micro-services that project directly to low-barrier, big data graph platforms for effective, realtime analytics. Both third-generation Graph Database and enterprise grade inference-engine oriented Knowledge Graphs are candidate targets for realtime transactional data projection resulting in many micro-services contributing to a singular view of the enterprise.

It is time to break down the human, technology, and resource consuming silos created by cobbling together platforms on a case-by-case basis. Keep the data—and information—flowing rather than allowing it to collect in a silo-induced lake.

BRSG consultants pursue ideas that scale, as well as that hold together well. Please reach out if we can be of service: info@brsg.io, or call 303.309.6240.