Today’s data-driven organisations are turning to Databricks for a cloud-based, open, unified platform for data and AI. Yet many companies struggle to unlock the value of the data they have in Databricks. To capitalise on the promise of a competitive edge through increased efficiency and insight, data scientists are turning to location to make sense of massive volumes of business data. Watch this on-demand to hear from The Spatial Distillery Co. and Databricks on how to leverage advanced location intelligence and enrichment solutions in Databricks to: - Simplify the complexity of location data and transform it into valuable insights - Enrich data with thousands of attributes for better, more accurate analytics, AI, and ML models - Leverage the power of Databricks to integrate geospatial data into business processes for real-time answers - Create more meaningful and timely customer interactions by streamlining customer-facing and operational tasks

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4. Databricks
The data and AI company

5. 5000+
Across the globe
CUSTOMERS
Lakehouse
One simple platform to unify all of
your data, analytics, and AI workloads
The data and AI company
ORIGINAL CREATORS

6. We’re working with enterprises in every industry
Energy & Utilities Digital Native
Healthcare & Life Sciences Financial Services
Manufacturing & Automotive Media & Entertainment
Public Sector Retail & CPG

7. Every company is becoming a data company
ML-driven actuarial
modeling increases the
predictability & accuracy
of insurance pricing
Millions of genomic
variants analyzed in 15
minutes, leading to 2 new
drug targets for neuro-
degenerative diseases
Personalize the gaming
experience with tailored
offers for 67M+ gamers
Increased audience
engagement with an
Emmy winning voice-
powered experience
Support contact tracing
for over 60 million UK
citizens and predict the
spread of COVID-19

8. Atlassian uses Databricks to deliver personalized services that increase customer
value while driving down operational costs.
$60 Million
increase in support
& service revenue
$12 Million
annual savings in
compute costs
Use Cases
• Customer support & service experience
● Marketing personalization
● Anti-abuse & fraud detection
Challenges
● Disjointed data sources and on-prem
architecture slowed innovation and
customer-level reporting.
Solution
• Lakehouse architecture with unified data
supports new reporting services and ML
personalization to 30k customers
• Redash for SQL Analytics for internal
reporting + Tableau and Looker
integrations for customer dashboards
across all services
• Delta Lake underpins customer data
improving performance and enabling scale

9. Use Case
• Supply chain optimization
• On premise data warehouse was
slowing down the speed to
action data for decision making:
hard to find data; hardware
performance issues; high,
inflexible costs
Why Databricks?
• Unified data more easily
discoverable; streamed and
used in real time; stored in one
place; and shared internally or
externally throughout the
organization
• Data teams can now
collaborate on the same
platform
Impact
• Faster model training from 3
days to 3 hours
• Increased speed of data has
helped the business with faster
decision-making
• Cloud flexibility ensures ability
to scale costs with the
demands of the business

10. The future is here, it’s just not very evenly
distributed
$3.9T
83% CEOs say AI is a
strategic priority
Business value created
by AI in 2022
85% of big data
projects fail
87% of data science projects
never make it into production

11. Today, most enterprises struggle with data
Siloed stacks increase data architecture complexity
Data Warehousing Data Engineering Streaming Data Science & Machine Learning
Extract Load
Transform
Streaming data sources
Streaming Data Engine
Real-time Database
Analytics and BI
Data marts
Data warehouse
Structured data
Structured, semi-structured
and unstructured data
Structured, semi-structured
and unstructured data
Data Lake
Data prep
Data Lake
Machine
Learning
Data
Science

12. Today, most enterprises struggle with data
Siloed stacks increase data architecture complexity
Data Warehousing Data Engineering Streaming Data Science & Machine Learning
Extract Load
Transform
Streaming data sources
Streaming Data Engine
Real-time Database
Analytics and BI
Data marts
Data warehouse
Structured data
Structured, semi-structured
and unstructured data
Structured, semi-structured
and unstructured data
Data Lake
Data prep
Data Lake
Machine
Learning
Data
Science
Amazon Redshift Teradata
Azure Synapse Google BigQuery
Snowflake IBM Db2
SAP Oracle Autonomous
Data Warehouse
Hadoop Apache Airflow
Amazon EMR Apache Spark
Google Dataproc Cloudera
Jupyter Amazon SageMaker
Azure ML Studio MatLAB
Domino Data Labs SAS
TensorFlow PyTorch
Apache Kafka Apache Spark
Apache Flink Amazon Kinesis
Azure Stream Analytics Google Dataflow
Tibco Spotfire Confluent
Disconnected systems and proprietary data formats make integration difficult

13. Today, most enterprises struggle with data
Siloed stacks increase data architecture complexity
Data Warehousing Data Engineering Streaming Data Science & Machine Learning
Extract Load
Transform
Streaming data sources
Streaming Data Engine
Real-time Database
Analytics and BI
Data marts
Data warehouse
Structured data
Structured, semi-structured
and unstructured data
Structured, semi-structured
and unstructured data
Data Lake
Data prep
Data Lake
Machine
Learning
Data
Science
Amazon Redshift Teradata
Azure Synapse Google BigQuery
Snowflake IBM Db2
SAP Oracle Autonomous
Data Warehouse
Hadoop Apache Airflow
Amazon EMR Apache Spark
Google Dataproc Cloudera
Jupyter Amazon SageMaker
Azure ML Studio MatLAB
Domino Data Labs SAS
TensorFlow PyTorch
Apache Kafka Apache Spark
Apache Flink Amazon Kinesis
Azure Stream Analytics Google Dataflow
Tibco Spotfire Confluent
Disconnected systems and proprietary data formats make integration difficult
Data Scientists
Data Engineers
Data Analysts Data Engineers
Siloed data teams decrease productivity

14. Data
Warehouse
Lakehouse
One platform to unify all of
your data, analytics, and AI workloads
Data
Lake

15. Data
Warehouse
Data
Lake An open approach to bringing
data management and governance
to data lakes
Better reliability with transactions
48x faster data processing with indexing
Data governance at scale with fine-
grained access control lists

16. Structured Semi-structured Unstructured Streaming
Lakehouse Platform
Data Engineering
BI & SQL
Analytics
Real-time Data
Applications
Data Science
& Machine Learning
Data Management & Governance
Open Data Lake
SIMPLE OPEN COLLABORATIVE

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