07, Dec 2020
As businesses across the world continue to grow through the power of data science and machine learning,
deficiency is emerging in the systematic integration of data.
Ever expanding data sources, batch data movement, rigid transformation workflows, growing data volume,
distribution of data across multi and hybrid environments all make integration of data an increasingly
Though the process of data collection from various sources itself is straightforward, enterprises must
integrate, process, curate, and transform all of those data with other sources and then deliver an
view of the customer, partner, product, and employee.
Is your head spinning yet?
An end-to-end data management process is an amalgamation of real-time connected data, self-service, and a
degree of automation, speed, and intelligence. Thus, it needs efficient and unconventional management
to reduce cost and manual efforts.
What is the value of a Knowledge graph in a world where businesses thrive on intelligence?
Knowledge graphs make it much easier for decision-makers to derive insights from the massive amount of data
Knowledge graph offers businesses all kinds of benefits, from self-service abilities and support to
data management. That includes ingestion, transformation, preparation, discovery, data catalog, integration,
governance, and security.
These graphs usually exist on top of the organizational data, linking them together, usually to enhance
knowledge of relationships between objects, events and abstract values.
Graph databases help human users, programmers and machines alike interpret data. Remember the good old days
using endless numbers of JOINs to query strictly defined rows and columns?
Mercifully, those days have gone the way of dialup connection.
Let’s do a countdown through the benefits and features of DataBlaze:
How do we leverage Knowledge Graphs for a data management platform like DataBlaze?
If you think of Knowledge Graph as the tool that defines relationships between key business resources,
operations and stakeholders, think of DataBlaze as the system that prepares data to be represented sensibly on the
graph and helps you derive insights out of it.
If Knowledge Graph is the story, DataBlaze is the storyteller.
DataBlaze provides unique and structured solutions. Its end to end management capabilities provide a
solution for your data management troubles.
#5 Insightful graph algorithms that pave the way for efficient decision making:
- Graph embeddings
- Community detection
- Graph similarity
#4 Analytical Models accelerated through Knowledge graphs:
- Customer 360
- Customer intelligence
- Risk analytics
- IoT analytics
#3 Crucial ways in which DataBlaze uses knowledge graphs to save your business precious time and effort:
- Weaves together your organization’s structured and unstructured data into an Enterprise Data Fabric.
- Effectively connects, harmonizes and governs data in your data lake while also eliminating the need
stitch together multiple data tools and write custom code.
- Uses data science algorithms like correlation, profiling, distributions and entropy analysis to
automatically connect and segment data for analysis.
#2 places where businesses use Knowledge graph :
- Google searches – When you search a movie title on Google and it shows similar movies, cast
movies by same director etc., that’s Knowledge graph at play. Google uses Knowledge graphs to
options to their users quickly and efficiently.
- Amazon searches – When we ask amazon to show us the best leather shoes for $200 – it calls
knowledge graph to understand how it can best answer this demand.
#1 place you definitely need a Knowledge graph
- Your enterprise-level business intelligence.
Imagine if, in addition to having connected data sources, applied strategic templates, and multiple
effectively-run pipelines, your data was also easy to understand and question.
It’s not a fantasy! With DataBlaze, you can actually get all of that. Yes, really.
Seeing is believing. Contact
today for a demo!