Float Float

Float

Source

Use Dataddo's Float connector to explore any data available via the official API of Float. Access hundreds of metrics and attributes, from basic to advanced. Build and blend custom datasets directly in Dataddo, then send them anywhere.

DATA FIELDS

Explore Data You Can Extract from Float

Data Category

Need fields you don't see?

Let us know and we'll add them to the connector. Just send a request here..

Available Attributes (133)

Attribute
id

Account ID

string
department_filter_id

Department Filter ID

string
created

Created

datetime
modified

Modified

datetime
name sensitive

Name

string
email sensitive

Email

string
account_type

Account Type

string
view_rights

View Rights

integer
edit_rights

Edit Rights

integer
active

Active

integer
id

Client ID

string
name

Name

string
department_id

Department ID

string
parent_id

Parent ID

string
name

Name

string
id

Holiday Id

string
date

Date

datetime
end_date

End Date

datetime
name

Name

string
id

People ID

string
department_id

Department ID

string
people_type_id

People Type ID

integer
start_date

Start Date

datetime
end_date

End Date

datetime
created

Created

datetime
modified

Modified

datetime
name sensitive

Name

string
email sensitive

Email

string
job_title

Job Title

string
department_name

Department Name

string
notes

Notes

string
avatar_file

Avatar File

string
work_days_hours

Work Days Hours

string
tags_name

Tags Name

string
tags_type

Tags Type

string
auto_email

Auto Email

integer
employee_type

Employee Type

integer
active

Active

integer
default_hourly_rate sensitive

Default Hourly Rate

float
people_id

People ID

string
department_id

Department ID

string
people_type_id

People Type ID

integer
start_date

Start Date

datetime
end_date

End Date

datetime
name sensitive

Name

string
department

Department

string
scheduled

Scheduled

string
capacity

Capacity

float
timeoff

Timeoff

float
billable

Billable

float
non_billable

Non billable

float
overtime

Overtime

float
unscheduled

Unscheduled

float
default_hourly_rate sensitive

Default hourly rate

float
wk_day_hrs

Working Day Hrs

float
employee_type

Employee Type

integer
phase_id

Phase ID

string
project_id

Project ID

string
start_date

Start Date

datetime
end_date

End Date

datetime
created

Created

datetime
modified

Modified

datetime
name

Name

string
color

Color

string
notes

Notes

string
non_billable

Non Billable

integer
status

Status

integer
active

Active

integer
budget_total

Budget Total

float
default_hourly_rate

Default Hourly Rate

float
id

Project ID

string
client_id

Client ID

string
project_manager

Project Manager

string
created

Created

datetime
modified

Modified

datetime
name

Name

string
color

Color

string
notes

Notes

string
tags

Tags

string
budget_type

Budget Type

integer
non_billable

Non Billable

integer
tentative

Tentative

integer
active

Active

integer
all_pms_schedule

All Pms Schedule

integer
budget_total

Budget Total

float
default_hourly_rate

Default Hourly Rate

float
start_date

Start Date

datetime
end_date

End Date

datetime
project_id

Project ID

string
client_id

Client ID

string
name

Name

string
client

Client

string
scheduled

Scheduled

float
billable

Billable

float
non_billable

Non-billable

float
id

Task ID

string
project_id

Project ID

string
phase_id

Phase ID

string
people_id

People ID

string
created_by

Created By

string
modified_by

Modified By

string
start_time

Start Time

datetime
start_date

Start Date

datetime
end_date

End Date

datetime
created

Created

datetime
modified

Modified

datetime
repeat_end_date

Repeat End Date

datetime
name

Name

string
notes

Notes

string
people_ids

People IDs

string
status

Status

integer
repeat_state

Repeat State

integer
priority

Priority

integer
hours

Hours

float
timeoff_type_id

Timeoff Type Id

string
created_by

Created By

string
timeoff_type_name

Timeoff Type Name

string
color

Color

string
timeoff_id

Timeoff Id

string
timeoff_type_id

Timeoff Type Id

string
modified_by

Modified By

string
created_by

Created By

string
start_date

Start Date

datetime
end_date

End Date

datetime
created

Created

datetime
modified

Modified

datetime
repeat_end

Repeat End

datetime
start_time

Start Time

string
timeoff_notes

Timeoff Notes

string
people_ids

People Ids

string
repeat_state

Repeat State

integer
full_day

Full Day

integer
hours

Hours

float

Pricing

See all Dataddo plans

Compare Dataddo's flow-based pricing tiers side by side and start your 14-day free trial.

View pricing
One Platform to Connect All Your Data

Why Dataddo?

One Ingestion Layer for SaaS, Databases, and Files

One Ingestion Layer for SaaS, Databases, and Files

Most teams use multiple tools and “spaghetti code” for ingestion, depending on the type of sources and loading patterns. Dataddo brings this under one control plane and one predictable pricing structure. 400+ connectors included.

Built for Cloud and On-Premise Environments

Built for Cloud and On-Premise Environments

Run Dataddo in both cloud and hybrid on-prem configurations. The control plane stays in the cloud; your data never leaves your perimeter. Supports segmented and private networks, and legacy systems including DB2, Informix, and Sybase.

Full API Control - No UI Required

Full API Control - No UI Required

Dataddo is built API-first. Use the UI when you want it; bypass it entirely when you don’t and orchestrate your pipelines programmatically.

Managed Ingestion Operations. We Own the Reliability.

Managed Ingestion Operations. We Own the Reliability.

Dataddo takes operational responsibility for your ingestion layer. We manage connector maintenance, handle API changes from source systems, monitor pipelines proactively, and execute backfills and recovery. Your engineering team doesn’t have to.

Full Visibility Into Every Data Flow

Full Visibility Into Every Data Flow

Dataddo gives you complete observability across your ingestion layer: pipeline logs, run histories, data lineage, and audit trails. Know what moved, when it moved, what changed, and why. Built for environments where explainability and accountability are not optional.

The Data Foundation Your AI Needs

The Data Foundation Your AI Needs

Enterprise AI depends on a governed, secure data layer. Dataddo consolidates SaaS, database, and file data into a unified managed pipeline, delivering to vector databases, feature stores, and data lakes, with native sensitive data hashing.

See All Platform Benefits
Case Studies

See What Other Organizations Have Achieved with Dataddo

24

eshops

to one data warehouse
for comprehensive insights

3x

Faster

data
collection

37.5%

reduction

of infrastructure bill
on average

Testimonials

Our Customers Love Us

G2 Implementation Winter 2025

Amalia Bornstein

Global Social Content and Marketing Data Analyst

Uber Eats

“The data team at Uber Eats appreciates Dataddo's user-friendly interface that is designed for operation by non-technical team members in an order to minimalize the need for excessive training to support efficient project delivery.”

G2 Implementation Winter 2025

Andrew Hart

Chief Operations Officer

Sat 7

“Working with Dataddo has greatly simplified our reporting and given us access to trend data and insights that we were previously unable to generate.”

G2 Implementation Winter 2025

Vahan Petrosayan

Director of IT & Infrastructure

Search Engine Journal

“With Dataddo, all of my questions get answered faster …[and it's] fun to play with data now.”

G2 Implementation Winter 2025

Michael Guntenaar

CTO

ID&T Group

“Dataddo opens up gates and takes away the hurdles of working with data.”

G2 Implementation Winter 2025

Laurent Partouche

CPO

FoodChéri & Seazon

“We chose Dataddo for its user-friendliness, automatic transformations, clear pricing policy, and the quality of the human relationship that was established from our first exchanges.”

G2 Implementation Winter 2025

Natheer Maloon

Technology Solutions Manager

Boldr

“Dataddo support proved immensely valuable throughout the implementation phase. 9.5 out of 10.”

G2 Implementation Winter 2025

Zdeněk Hejnak

Data Development Team Leader

Livesport

“We save about 70% of the time it would otherwise take to ingest all our data, or 3-4 full-time equivalents, and spend this much more time on data analytics and activation. We only have one full-time data engineer, who does more than just collect data, while our BI team consists of 11 members.”

G2 Implementation Winter 2025

Greg Senior

Business Operations Manager

Farm Focus

“Appreciate all the help and support for us. A refreshing level of service from a tech company! Thank you!”

G2 Implementation Winter 2025 G2 Performer Winter 2025 Google Cloud Partner Tableau Technology Partner AWS Partner Network Gartner Cool Vendor