The modern
data mindset

Making data-driven decisions a reality across your organization.

The world is awash with data, with analytics helping business leaders make smarter decisions every day. But without data integration, those insights are siloed and limited.

Learn how data integration and a modern data mindset allows your organization to gain a comprehensive view of business operations and customer interactions, while unlocking the secret to more robust, scalable insights and happier teams.

This free guide gives you the insights to drive more integrated business decision-making, for more powerful data-driven results.

01

How developed is your data hierarchy?

A piecemeal approach to data integration misses vital foundations and can undermine your entire data strategy. Which of these elements do you have in place? Switch them on to complete the data hierarchy.

01
Data extraction & loading
Assemble a data stack
No
Yes
02
Data Modeling & transformation
Build hub-and-spoke data team
No
Yes
Publish data governance standards
No
Yes
03
Visualization & decision Support
Hire an analytics PM
No
Yes
Train managers on data literacy
No
Yes
04
Data activation
Build systems to operationalize data
No
Yes
05
AI/ML
Hire data scientists
No
Yes
Build predictive models
No
Yes
02

See the impact of adopting an ELT workflow

In all but a few niche cases, ELT is a superior data integration architecture to ETL. Lean, agile data teams can use ELT to address a wide range of challenges related to data integration.

Leverage automation

Leverage automation
ETL
ELT
Programmatic control over data ingestion

Programmatic control over data ingestion

Automated scheduling

Automated scheduling

Analyst-friendly

Standardized data models

Easy to use

No-code data integration

Usable out-of-the-box/off-the-shelf

Usable out-of-the-box/off-the-shelf

Automatic schema migration

Automatic schema migration

Low or zero configuration

Low or zero configuration

Fully managed

Fully managed services

Data integrity and reliability

Data integrity and reliability
ETL
ELT
Automated scheduling

Supports robust data governance tools

Low maintenance

Compliance w/ regulatory and security standards

Programmatic control over data ingestion

Pipeline insulated from transformation failure

Analyst-friendly

Create new model without rebuilding data pipeline

Usable out-of-the-box/off-the-shelf

Ingest full data model; access to raw data

Prepare to
scale

Prepare to scale
ETL
ELT
Programmatic control over data ingestion

SQL-based data modeling

Automated scheduling

Cloud-native

Analyst-friendly

Avoid building and managing infrastructure

Usable out-of-the-box/off-the-shelf

Use with pre-built data models

Usable out-of-the-box/off-the-shelf

Short load time

See how workflows differ.

Leverage automation
ETL
ELT
Programmatic control over data ingestion

Programmatic control over data ingestion

Automated scheduling

Automated scheduling

Analyst-friendly

Standardized data models

Easy to use

No-code data integration

Usable out-of-the-box/off-the-shelf

Usable out-of-the-box/off-the-shelf

Automatic schema migration

Automatic schema migration

Low or zero configuration

Low or zero configuration

Fully managed

Fully managed services

Data integrity and reliability
ETL
ELT
Automated scheduling

Supports robust data governance tools

Low maintenance

Compliance w/ regulatory and security standards

Programmatic control over data ingestion

Pipeline insulated from transformation failure

Analyst-friendly

Create new model without rebuilding data pipeline

Usable out-of-the-box/off-the-shelf

Ingest full data model; access to raw data

Prepare to scale
ETL
ELT
Programmatic control over data ingestion

SQL-based data modeling

Automated scheduling

Cloud-native

Analyst-friendly

Avoid building and managing infrastructure

Usable out-of-the-box/off-the-shelf

Use with pre-built data models

Usable out-of-the-box/off-the-shelf

Short load time

03

Avoid the integration iceberg

Data pipelines are like icebergs. On the surface, they’re simple. But the majority of the work required is hidden from view, lurking beneath the surface. Data integration is a complicated task, with hidden depths and complexities.

Automated ELT allows you to start syncing data in minutes.

1
Connect a data warehouse
2
Add connectors
3
Supply credentials
4
Begin syncing

Data should update incrementally, starting with the most recent records. Analyze at your convenience.

Move data from source
to destination
Data modeling
Reports and dashboards
Water

If you do it all yourself...

Explore and document source data
Automated scheduling
and triggers
Incremental
updates
Idempotence
Lossless replication
Logic and process isolation
Explore and document source data
Automated scheduling
and triggers
Incremental
updates
Idempotence
Lossless replication
Logic and process isolation
Distributed architecture
Role-based access control
Security and regulatory compliance
Automated schema migration

Typical Time Spent

1 Week
2 Weeks
4 Weeks
6 Weeks
8 Weeks
10 Weeks
12 Weeks
14 Weeks
16 Weeks
18 Weeks
20 Weeks
24+ Weeks
1 Week
2 Weeks
4 Weeks
6 Weeks
8 Weeks
10 Weeks
12 Weeks
14 Weeks
16 Weeks
18 Weeks
20 Weeks
24+ Weeks
04

Consider the total cost of ownership

There are tradeoffs between building your own data integrations, and committing to maintain them over time, or buying a solution as a service. In most cases, it makes more sense, saves time, and lowers costs to buy an off-the-shelf solution.

TCO Calculator

You will spend $629,000 in 75 weeks building and maintaining something you could deploy faster with Fivetran.*

Connectors to build
0
Average engineering salary
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* This is an approximation. Contact us for an accurate calculation.

05

Discover the secret to a high-performing data team

Data professionals strive to make sense of data, not wrangle it. A modern data stack enables higher-value uses of expensive data engineering, data science and analytics time.

Most valuable tasks
Mining data for patterns
No
Yes
Refining algorithms
No
Yes
Building training sets
No
Yes
Least valuable tasks
Cleaning/organizing data
No
Yes
Collecting data sets
No
Yes
Other
No
Yes
TIME SPENT
PAIN INDEX

Source: Crowdflower via Forbes

06

Download the full guide

Get the insights to drive more integrated business decision-making, for more powerful data-driven results.

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