Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following:
- Your organization’s data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
2. Sean Martin, CTO
Cambridge Semantics Inc.
January 2023
Data Strategy Best Practises
Where do Knowledge Graphs fit in?
3. Copyright 2023. Cambridge Semantics Inc
Emerging modern data management architectures
What people say..
1
Data Mesh
● a human and product-centric approach
● enable scaling by giveing discrete teams control over how their
data is stored and managed
● experts in certain business domains are in charge of preparing
& hosting specific data sets, governance, management and
processes
● data is seen as a product (value of the integration, SLA’s etc).
● to enable centralized analytics, reporting, BI and ML efforts,
APIs are used to connect to different data sources
● In a data mesh, each business unit is responsible for creating
and maintaining its own data and sharing it with others Instead
of using a single virtual layer to manage disparate sources, a
data mesh uses multiple domains, with each domain specific to
the needs/purpose of the domain
● more completely embraces distributed data governance and
management
● bottom-up process
● automation?!
● abstracts data from the location where it is created or stored
● uses metadata to automatically connect disparate data
● provide a single view of an organization’s data estate
● understand how datasets and metadata are related
● virtualization
● the technology eliminates the need for bulk transfers of data?!
● consists of a single source of truth
● is about eliminating humans from the process as much as possible
● does not require replacement of existing infrastructure but instead
adds a layer of additional technology above the existing
infrastructure that performs metadata management and inference
● data management is unified and not the actual storage
● semantics enable the formation of a knowledge graph that
deepens the connection across datasets
● top-down control
Data Fabric
What people do seem to agree on is that the two approaches are not mutually
exclusive and that customers can combine aspects of each to best suit their needs.
OR
4. Copyright 2023. Cambridge Semantics Inc
RDBMS/OLTP Big Data / Hadoop Document Repositories
Flat Files
Third Party
Legacy
Mart
Mart
ETL
Data Warehouse
Data Lake
XML • JSON • PDF
DOC * WEB
Traditional BI Cloud
CUSTOMERS
PRODUCTS
CLAIMS
COMPOUNDS
Anzo delivers knowledge
graph as a lightweight data
integration overlay.
2
Copyright 2023. Cambridge Semantics Inc 2
5. Copyright 2023. Cambridge Semantics Inc
Knowledge graphs
3
Connect siloed data. Simplify complicated data.
Simplifies access to complex data to address
unanticipated questions
Quickly profiles, connects and harmonizes data
from multiple sources, including unstructured
Presents tailored views, services and
experiences to different personas with
conceptual models
Flexibly accommodates new data sources
and use cases on the fly, with minimal impact
Cambridge Semantics enables scalable OLAP
style knowledge graphs capable of accomodating
enterprise data sources and use cases
6. Copyright 2023. Cambridge Semantics Inc
12.2 Pharmacodynamics
Treatment with glucocorticosteroids, including
UCERIS rectal foam, is associated with a
suppression of endogenous cortisol
concentrations and an impairment of the
hypothalamic-pituitary-adrenal (HPA) axis
function.
Knowledge graphs are connected graphs of data and
metadata that richly model real-world entities
Appl_No Approval_Date Applicant
205613 10/07/2014
Valeant
Pharms
212379 10/18/2019 Foamix
… … …
ApplNo ProductNo DrugName ActiveIngredient
205613 10/07/2014
Valeant
Pharms
HYDROCHLORIDE
212379 10/18/2019 Foamix BUDESONIDE
… … … …
205613
APPLNO
Drug
CONTAINS
BUDESONIDE
ACTIVEINGREDIENT
UCERIS
DRUGNAME
Product
2MG/ACTUATION
STRENGTH
ABOUT
Pharmacodynamics
glucocorticosteriods
endogenous cortisol
SUPRRESION
TREATMENT
10/07/2014
Product
APPLICANT
Valeant Pharms
Application
205613
APPL_NO
isSponsor
Product
(Canonical)
4
DRUGS@FDA - Approved
360 view of every drug submission
○ Integrates 14 source systems
○ >300,000 Drugs
○ 70+ years of historical data
○ >8 million documents
8. Copyright 2023. Cambridge Semantics Inc
Cambridge Semantics for Industry 4.0
6
Connected Data for Digital Thread & Twins
As Designed As Manufactured As Used
▪ Cambridge Semantics was chosen as knowledge graph provider by
major European manufacturer for a next generation data platform
▪ This was part of a multi-year digital transformation initiative from the
company’s board
▪ The knowledge graph is used as an internal-use platform and
external customer engagement / monetization solution
▪ Helps connect data across operations, manufacturing, etc. for 70%
efficiency gains on initial use cases; Savings >$100M
Diagnosis Claims Operations
Engineering Data ePLM
Industry 4.0
Knowledge
Graph
BOM
SAP_Materials
Drawing
Electronic
Layouts
PLC
Production
Line
Plant
Material
Product
Component
Bin
Supplier
Process
Component Vehicle
Claim
Diagnostic
MACHINES | FACTORY FLOOR
We are at the second wave of the semantic technology. The first wave
began with the semantic web. The tools have matured since then. Today
you can process large knowledge graphs on reasonable hardware.
In the past, you had a graph database and some semantic modeling tool,
and you had to cobble that together. But now that is offered in a platform
fashion by the vendors. You have a lot of capabilities – like connections to
the data sources, modeling, mapping and blending tools, and last but not
least the analytics on top of the data.
It is a huge step forward.
-Customer speaking on a panel of
Cambridge Semantics customers at
The Knowledge Graph Conference
“
“
9. Copyright 2023. Cambridge Semantics Inc
Further reading
7
https://www.amazon.com/Data-Management-Scale-Modern-Architecture-dp-1098138864/dp/1098138864/
Data Management at Scale: Modern Data
Architecture with Data Mesh and Data Fabric
2nd Edition
by Piethein Strengholt
Publisher(s): O'Reilly Media, Inc.
ISBN: 1098138864
The Rise of the Knowledge Graph
by Sean Martin, Ben Szekely, Dean Allemang
Released March 2021
Publisher(s): O'Reilly Media, Inc.
ISBN: 9781098100391
https://info.cambridgesemantics.com/the-rise-of-the-knowledge-graph-oreilly