You connect. The product does the rest.
Data360 reads your data, checks what you can trust, builds your reports and acts on what matters — all in one place.
- 9
- setup steps
- 6
- product stages
- 7
- ways to bring data in
- 4
- honest labels
Done once, and done for good
Connect → Act
Snowflake, S3, PostgreSQL, MySQL, Odoo, Salesforce, a file
Sure, to confirm, missing, not possible
From your sources to action taken
One continuous chain, not a stack of tools.
Your systems, exactly as they are
Snowflake
Amazon S3
PostgreSQL
MySQL
Odoo
Salesforce- A file from your computer
Amazon S3, PostgreSQL and MySQL come with a paid plan. Coming next: Google Cloud Storage, SFTP, Azure Blob Storage, Oracle, Databricks and Apache Iceberg. Tell us which you need
Six stages, one surface
Pick a stage to see what happens there.
You do
Connect or import your data
Data360 does
Reads your tables where they live
You get
All your data in one place
What the AI reads in your columns
From raw columns to the figures worth following, in five steps.
- 1
Columns found
date_ventecolumnmontant_htcolumn
- 2
What each one is
date_ventea datemontant_htan amount
- 3
What it describes
id_clientCustomercode_magasinStore
- 4
How they link
SaleCustomerSaleStore
- 5
Figures to follow
Revenue per storereadyNet margincosts missing
Can’t be worked out? It is said, never guessed.
Set up in 9 steps
What the setup looks like, screen by screen.
- 01
Welcome
What Data360 will do for you, in a few steps.
Setup wizard · Welcome
Welcome to Data360
Nine steps, done once.
- Rebuild how your business works
- Measure what you can rely on
- Generate your 360° control tower
- 02
Business context
Your industry and your scope.
Setup wizard · Business context
What industry are you in?
- 03
Your goals
What you want to track, steer and improve.
Setup wizard · Your goals
What do you want to follow?
0 selected
- 04
Data sources
Snowflake, Amazon S3, PostgreSQL, MySQL, Odoo, Salesforce or a file from your computer.
Setup wizard · Data sources
Where does your data live?
- Snowflake
- Amazon S3
- PostgreSQL
- MySQL
- Odoo
- Salesforce
- A file from your computer
- 05
Connection
Sign in to your source, or drop a file.
Setup wizard · Connection
Connect your data
- Account
- acme
- Signed in as
- reports@acme.com
- Tables
- Sales · Stores · Products
Connected
Data360 reads your data where it lives, keeps only what your reports need, and writes only what you ask for.
- 06
Data analysis
Done for youWhat your tables hold, and what you can trust.
Setup wizard · Data analysis
Reading your data…
0%
- Connecting to your data
- Reading your tables
- Checking what is missing or counted twice
- Recognising what each column holds
- Working out how your tables fit together
- 0
- Rows read
- 0
- Columns kept
- 07
Proposed model
Done for youHow your tables fit together, each link checked.
Setup wizard · Proposed model
Proposed model
- Customerwho or what✓ 98% sure
- Productwho or what✓ 96% sure
- Salewhat happens✓ 94% sure
- Storewho or what✓ 91% sure
- 08
Proposed reporting
Done for youThe reports recommended for your business.
Setup wizard · Proposed reporting
Proposed reports
4 reports
See which stores carry the month
Know which products actually make money
Catch empty shelves before customers do
Data health
- 09
Go live
What will be created, then one click to go live.
Setup wizard · Go live
What happens when you activate
- Reports to create
- 3 + Data health
- Tables used
- 2
- Kept on our side
- Only what reports need
Steps 6 to 8 arrive already built.
- 6Data analysis
- 7Proposed model
- 8Proposed reporting
Illustrative figures.
Four labels, and never a grey area
Every figure says how sure it is.
- Sure ✓
High confidence, and inspectable
The suggestion is applied by default — but the formula, the source and the sample stay one click away.
Net revenue
98%Sales amounts, minus discounts
From your Sales table, in Snowflake
- To confirm?
Only when the ambiguity is material
A question is asked only when the choice actually changes a figure you steer by. Not three hundred columns to approve.
Which date counts for revenue?
- Order date
- Delivery date
Gap between the two · €214k for the quarter
- Missing, and useful
What more data would unlock
Not a complaint, a quantified opportunity. You decide whether the effort is worth it.
Connect your purchase costs to unlock:
- Gross margin
- Margin per item
- Store profitability
- + 4 more figures
Estimated effort · 1 source, ~ 20 min
- Not possible
Why a figure cannot be worked out
No estimate dressed up as a fact. The exact reason is shown, along with what it would take to make it possible.
Customer satisfaction score
n/aNo connected source holds a survey or a customer rating. This metric cannot be derived — so it is not estimated.
To make it possible · connect a survey tool
Data quality as a business deliverable
A report your managers can read, measured again whenever you re-check.
Data health — today
Overall health score
87 / 100
Today · fit to act on
Trend · last 10 checks
+18 points over ten checks
Highest-payoff fix
Removing customers recorded twice fixes retention and four other figures.
Suggested owner · whoever keeps your customer list
Checks run today
- Is the data recent enough?
- Is anything important missing?
- Is anything counted twice?
- Does every sale point to a known store and product?
- Do sales and invoices agree?
- What each problem costs
The rule never changes: no problem is shown as a score on its own. "Completeness 87%" means nothing. "Today's regional ranking leaves out a store" can be acted on.
Illustrative figures.
A technical problem is not a decision
Pick a finding: what it costs the business appears opposite.
What the check found
What an executive reads
The network comparison for today leaves out a store and may distort the regional ranking.
Every consequence carries its fix and its owner.
The answer contract
Five parts, always the same. No evidence, and the answer says so.
"Why is margin falling in the South region this month?"
Answer
South margin is down −2.4 points for the month, or −€118k of gross margin.
Why
- Promotions extended on 3 best-selling products61%
- Higher supplier purchase costs27%
- Adverse product mix at month end12%
Share of the drop each cause explains.
Evidence
- Sources
- Your sales, purchases and promotions
- Period
- 1st to 31st of this month
- Scope
- South region · 14 stores
- Formula
- (Sales − cost of goods sold) ÷ sales
- Volume
- 412,806 sales lines
- Freshness
- Read 3 hours ago
Limit / Confidence
Discounts given at checkout are not broken down by product in your data. The share attributed to promotions is therefore estimated at receipt level, not item level — the ranking of causes holds, their exact weighting does not.
Action
Every action stays bounded by the permissions of the user who triggers it.
Illustrative figures.
An analysis that triggers nothing changes nothing
Six things Data360 does with what it finds, each limited to what your role allows.
What an alert is made of
Seven plain fields, on one page.
Open a field to see what it guarantees.
New alert · South margin
7 / 7 fields filled inEach crossing is told once, so an alert you set never turns into noise.
Guardrails
Built into Data360, not left to a setting.
Your data, where it lives
Data360 reads your data where it lives, keeps only what your reports need, and writes only what you ask for.
A small working copy
Up to 5,000 rows per table, kept only to draw your reports.
Formula shown
A figure comes with how it is worked out, and where from.
Permissions respected
No action beyond the permissions of whoever triggers it.
Model versions kept
Every version of your model is kept, and you can go back to one.
A history you can read
Who joined, left or changed role — and how each run went.
Personal details spotted
Names, emails and phone numbers are flagged, and you can hide them from reports.
The best way to judge the product is to see it on your own data.
Your business, your data, your goals.