Overview


Spreadsheet tools are limited when it comes to dealing with listings. Because they are built around worksheets and designed for accounting purposes, they have no data structure. Unlike [databases](/learn/spreadsheet/difference-between-spreadsheet-database), spreadsheet tools can't have data schema and data constraints. As a result, simple data operations like [merging duplicates](/how-to/excel-merge-duplicates) or consolidating listings are not available with spreadsheets.

Nevertheless, Microsoft Excel or Google Sheets are still our go-to applications when we have to quickly load a list of contacts, companies, etc. to perform cleaning, filtering, etc. because they are so easy to use!

Datablist aims to bring database features and data structures while borrowing spreadsheet user-friendliness.

## Datablist glossary

- **Workspace** - A Datablist account is linked to a workspace that is home to all your collections. A workspace can have any number of collections.
- **Collection** - A collection contains items that share a similar data structure. Collections can store lists of sale leads, customers, companies, partners, etc. [See collections documentation](/docs/collections).
- **Item** - An item is a data record. Items inherit their data schema from the collection they belong to.  [See items documentation](/docs/items).


## Datablist layout
![Datablist Main Layout](/docs_images/getting-started/datablist-layout.png#2159x1275)

### Sidebar

From the sidebar, you can access your collections in Datablist. Click on a collection to open it, drag and drop it on another to create a collection folder.
At the top, you see a summary of your profile information. By clicking on your profile, you can go to your company and user details page.

### Collection Header

Once on a collection, a header appears for managing it. Edit its name, icon, properties from this header. [See collections documentation](/docs/collections).


### Data Table

The data table is essential to work with data. It shows your collection data in a spreadsheet-like table. Move between cells with keyboards, use copy/pasting shortcuts, and more.

Press enter to edit a cell or click on the **Expand** icon to open an item in the detail drawer.

Select items by clicking the checkboxes on the left to delete/merge/export the items and to show the action launcher.


### Drawer

![Datablist Drawer](/docs_images/getting-started/datablist-layout-drawer.png#2154x1279)

The drawer is used to edit an item and to configure options before running an action. It's shown over the data table so it's easy to get back to the listing.

### Actions Launcher

![Datablist Actions Launcher](/docs_images/getting-started/datablist-layout-actions-launcher.png#2155x1277)

All items sharing the same data structure inside a collection open several possibilities. One of them is to run actions on your items to interact with third parties APIs. Once at least one item is selected (and you are a registered user), the actions launcher appears to show Datablist's actions catalog.

## Datablist storage basics

Datablist leverages the user's browser storage to store and manage data.

In recent years, modern web browsers have become platforms to build rich interactive applications. Email clients, spreadsheet tools, or text editors are examples of modern applications that have moved to be run inside web browsers. To support this trend, new features and capabilities were created to persistently store data inside a user's browser.


> **To know more**<br/>
> Datablist underlying storage technology is called IndexedDB. [Click here to learn more about it](https://developer.mozilla.org/en-US/docs/Web/API/IndexedDB_API).


Learn more about Datablist, a spreadsheet alternative to manage your listings.

An introduction to Datablist concepts

What's Datablist?


In Datablist, your data is structured with collections that contain items. All items inside a collection get their data structure from the [collection properties](/docs/properties).

For example, a collection can hold people's data to manage contacts (for subscribers, leads, or employees listings). Another collection can be used to store websites (for b2b prospects, competitor websites, Venture Capital funds, etc.).

Collections are linked to your account workspace and a workspace can have an unlimited number of collections.


## Create a collection

To create a new collection, click on the **+** button in the sidebar.

When you create a new Collection, it'll be named "Untitled Collection" with an 👋 by default. You can change this title and icon at any time by clicking on the title or the icon.

![New collection](/docs_images/getting-started/datablist-create-collection.png#1402x394)

A new collection has no data structure. To start adding items, you have to create properties. [Create them manually](/docs/properties) or import CSV/Excel files to create properties based on the file columns.

## Organize your data with nested collections

When you are dealing with too many collections, it's time to organize them. An easy solution is to group them together in a folder. Click and hold a collection in the sidebar, and move it over another one to create a parent folder.

<div class="content-video">
    <video
        autoplay muted loop playsinline controls width="100%" height="auto" class="d-block">
            <source src="https://storage.googleapis.com/public_datablist/website/docs/collections/datablist-collection-folder.mp4" type="video/mp4" />
    </video>
    <div class="text-center">Drag and drop to create folder</div>
</div>

## Delete a collection

To delete a collection, its properties, and all its items, select "Delete" in the menu available for each collection in the sidebar.

> **Important:** Datablist data structure is hierarchical. **Deleting a collection delete all its items.**

![Delete a collection](/docs_images/getting-started/datablist-delete-collection.png#1410x656)


### Deleting a collection folder.

The "delete" action is also available for collection folders. When deleting a collection folder, **all its collections and items will be deleted.**


Learn how to use collections to store contacts, leads, employees, or any kind of structured data.

Create, edit, delete collections in Datablist

Create Collections


Datablist lets you create flexible data structures for your collections with properties. Properties are used to store data and to sort and filter your items.

A property is defined with the following:
- **Name** - The name to be shown in the [data table](/docs/introduction#data-table) and the [drawer](/docs/introduction#drawer).
- **Data type** - What kind of data will be stored with the property. [Types can be texts, numbers, checkboxes, etc.](#create-a-new-property) Depending on its type, Datablist will perform data validation to ensure data input from users matches the data type.
- **Data constraint** - Unlike spreadsheet tools, it is possible to add data constraints on your property to [ensure unique values](#ensure-unique-values-for-a-property).

## Create a new property

Data structures for collections are flexible. You can create any number of custom properties that will be available to store values for your items.

Different property types are available to store texts, numbers, URLs, dates, etc. Depending on the property type, data validation will be done to ensure data is consistent.

On a new and empty collection, a shortcut button is shown to create a new property. Otherwise, click the **Manage properties** button on your [collection header](/docs/introduction#collection-header).

![Manage Properties](/docs_images/getting-started/datablist-manage-properties.png#1380x646)

![Add new property](/docs_images/getting-started/datablist-add-property.png#1452x684)

![Create new property](/docs_images/getting-started/datablist-new-property.png#1768x922)


### Data Types
#### Text

Simple text field for short and single line text.


#### Long Text

The Long-Text field is perfect for multiline text. Use it to store notes or descriptions. You can edit a long-text field value directly without leaving the [data table](/docs/introduction#data-table). Just press "Enter" to display a large editable text zone.

![Long Text edit in Data Table](/docs_images/getting-started/datablist-long-text.png#1702x882)

#### Email

Store email addresses. Open default mail client on click.

> **Validation:** Must be a valid email address.

#### Checkbox

A Checkbox is great to represent binary data: true/false or yes/no.

True values appear with a green checkmark. Empty and false values appear with an uncheck mark.
Clicking on the checkbox toggles its value.

![Checkbox in Data Table](/docs_images/getting-started/datablist-checkbox.png#1582x896)


#### Url

Clicking on a URL within a URL field will open up that page.

> **Validation:** Must be a valid url address.

#### Number

Data type to store numeric values. Numbers can be written with or without decimals and can be positive or negative.

> **Validation:** Must be a valid number

#### Date

Store date values (Day, Month, Year). When editing a date, a calendar widget is displayed to make it easy to select a specific date.

![Date in Data Table](/docs_images/getting-started/datablist-date.png#1580x912)

#### DateTime

Almost like date but store time in addition to the date (Day, Month, Year - Hour, Minute, Second).

![DateTime in Data Table](/docs_images/getting-started/datablist-datetime.png#1578x892)

#### Phone

Store phone numbers. Shortcut to open a phone client on click.

## Edit or delete property

To edit or delete a property, click the **Manage properties** button on your [collection header](/docs/introduction#collection-header), and click the **Edit or delete property button**.

Property name, data type and data constraint can be edited at any time.

> **Warning:** Deleting a property will delete the item's property's values.

![DateTime in Data Table](/docs_images/getting-started/datablist-edit-property.png#1556x886)

## Ensure unique values for a property

This enables powerful use cases like [prospect lists](/blog/prospect-list-building-growth-hacking) (email or website URL uniqueness), CRM, or user databases (email uniqueness). With this feature, you can combine listings based on a unique identifier.

When a property has a unique constraint, duplicate items will be avoided during [imports](/docs/import-data) and [manual creation](/docs/items#create-items-manually).

![Unique values constraint](/docs_images/getting-started/datablist-unique-values.png#1452x756)

Passport Numbers, Social Security Numbers, Email Addresses, Website URLs, Business Identification numbers, [Product GTIN](https://www.gs1.org/standards/id-keys/gtin), and the likes are good candidates to be defined with a unique constraint.


## Built-in properties

Datablist comes with two built-in properties:

- **Created At** - A DateTime property storing when the item has been created.
- **Updated At** - A DateTime property that tracks item last modification timestamp.

> **Note:** Those values are always tracked for your items, whether you choose to display their properties or not.

To display built-in properties, click on "Add property" and click on the wanted property.

![Add built-in property](/docs_images/getting-started/datablist-add-built-in-property.png#1696x938)

## Reorder properties

Properties are ranked. Their order is used both for [data table](/docs/introduction#data-table) columns display and for the [detail drawer](/docs/introduction#drawer).

To reorder properties, click the **Manage properties** button on your [collection header](/docs/introduction#collection-header) and use your mouse to drag the "Move" icon higher or lower.

![Reorder properties](/docs_images/getting-started/datablist-reorder-properties.png#2880x1800)


## Display or hide properties from data table

All collection properties are visible in the [item detail drawer](/docs/introduction#drawer). However, properties can be hidden from the [data table](/docs/introduction#data-table) to make the listing more readable.

New properties are visible in the data table by default. To hide a property or to show a hidden one, click on the "Manage Properties" buttons in the collection header and click the visibility toggle.

![Property Data Table visibility](/docs_images/getting-started/datablist-hide-property.png#1568x904)


## Change property column width

To resize a column, use your mouse to drag the column border to a new position, resizing it in the process.

![Resize column width](/docs_images/getting-started/datablist-resize-column-width.png#2880x1800)


## Advanced options

### Property Key

When creating a new property, under the "More options" section, a **Key** setting is available. The **key** is a "slug" string to be used in the [API](https://developers.datablist.com). It is autogenerated from the property's name and can be edited only when creating a new property. Once the propriety is created, the key becomes read-only.


Properties

Configure Properties


The most basic concept in Datablist is the **item**. Each item is represented with a row in the [data table](/docs/introduction). An item can represent anything: a contact, a lead, an employee, a website, etc.

Items are either created manually, by API, or by [importing an external file](/docs/import-data).

## Create items manually

Create a new item with the **New** button in the collection header.

> **Warning:** Your collection must have [properties](/docs/properties) before adding items manually.

![New item](/docs_images/getting-started/datablist-new-item.png#1344x588)

It opens the [drawer](/docs/introduction#drawer) on the right. Save your item quickly by pressing the **Enter** key or cancel and close the drawer with the **Esc** key.

![New item drawer](/docs_images/getting-started/datablist-new-item-drawer.png#2263x1416)

> **Keyboard Shortcut**<br/>
> The fastest way to create an item is with the keyboard shortcut **C** which will open up the new item drawer in your current collection.

### Data validation

Before creating an item, Datablist ensures the item's data validates all its [property data types](/docs/properties#data-types) and [data constraints](/docs/properties#ensure-unique-values-for-a-property).

![Property Validation](/docs_images/getting-started/datablist-item-property-validation.png#1476x708)

## Edit an item

To edit an item, you can open the detail view in the drawer or edit it directly in the table view with our spreadsheet-like interface.

**Edit directly**

On a cell, press **Enter** to edit an item and **Enter** or **Tab** to submit the changes. Press **Esc** to cancel them.

<div class="content-video">
    <video
        autoplay muted loop playsinline controls width="100%" height="auto" class="d-block">
            <source src="https://storage.googleapis.com/public_datablist/website/docs/items/datablist-edit-data-table.mp4" type="video/mp4" />
    </video>
    <div class="text-center">Edit by pressing Enter</div>
</div>


**Edit item in drawer**

Sometimes, having a form view to edit your items is more convenient. For example, if some of your [collection properties](/docs/properties) have been hidden from the data table. In the drawer, all item properties are shown.

![Open Drawer](/docs_images/getting-started/datablist-open-item.png#1322x542)


## Select items and top bar

On the left of the items, you can find a checkbox to select items. When at least one item is selected, buttons appear in a top bar.

Available buttons:
- **Delete items** - Will permanently delete selected items
- **Export items to CSV** - Generate a CSV file with the selected items
- **Merge items** - [Open Datablist Merging Assistant](/docs/merge-items)
- **Unselect** - Cancel selection

![Top bar buttons](/docs_images/getting-started/datablist-items-selected-bar.png#1378x558)

### Quick select

To quickly select items, you can use your mouse by clicking and holding it while moving over other checkboxes. Another solution is to check one checkbox and click on another one while pressing the **Shift** key. All items in between will be selected.

<div class="content-video">
    <video
        autoplay muted loop playsinline controls width="100%" height="auto" class="d-block">
            <source src="https://storage.googleapis.com/public_datablist/website/docs/items/datablist-select-items.mp4" type="video/mp4" />
    </video>
    <div class="text-center">Quick select items</div>
</div>

> **Tip:** Use the keyboard shortcut **Ctrl + a** to select all items


### Items count on search term or filtered listing

Datablist doesn't calculate the data table count when you use a [search term](#search-and-sort-items) or [filtered conditions](#filter-items) by default (for performance reasons).

But you can ask Datablist to run a count operation by clicking the "Select all" checkbox and then on the "All items selected" label.

![Count all items](/docs_images/getting-started/items/datablist-count-selected-items.png#1416x708)


## Search and sort items

Searching through your items is simple. Datablist performs a full-text search on all of your item property values in seconds.

The search input is located in the [collection header](/docs/introduction#collection-header). A fast way to start a search is using the keyboard shortcut **Ctrl + f**.

![Full text search](/docs_images/getting-started/datablist-full-search.png#1816x860)

Items can be sorted on any visible property by clicking on the property column. Property values can be sorted in ascending or descending order.

![Sort items by property](/docs_images/getting-started/datablist-items-sort.png#1816x892)


## Filter items

[Full-text search](#search-and-sort-items) looks for a term in all available properties. To filter your data on specific properties, use **Filter Conditions**.

Filtering is useful to:
- Find items that meet certain conditions
- Have a clean listing by excluding items
- [Filter a CSV file to extract specific rows](/csv-editor)

Filtering works by creating filter conditions on one or several properties.

### Add a filter condition

Add a filter condition by clicking the "Change filters" button in the [collection header](/docs/introduction#collection-header).

![Open Filters modal](/docs_images/getting-started/items/datablist-add-filter-condition.png#1633x547)

A filter condition is made of 3 elements:

- **A Property** - Any property in your collection.
- **An Operator** - The filter operator specifies how to compare the data with your filter value. Depending on the property data type, operators can be: *contains*, *is*, *is empty*, *is not empty*, numerical operators, date comparators, etc.
- **A Value** - The value to compare your item's property' data against.

> **Note**<br />
> Operators "**is empty**" and "**is not empty**" do not require a value.

**Click the "Apply" button to run your filter condition against your collection items.**

![Filters modal](/docs_images/getting-started/items/datablist-filters-condition-modal.png#1840x772)


### Combining several filter conditions

Filter conditions work in **AND** mode. Only items matching **all** filter conditions are displayed in your data table.

Use the "Add another filter" to add another filter condition.

![Combine several filter conditions](/docs_images/getting-started/items/datablist-combine-filter-condition.png#1836x914)

> **Feedback Wanted!** <br />
> Do you need more complex filtering? [Please share your use case with us](https://docs.google.com/forms/d/e/1FAIpQLSeAZfqCjOg-ok7yYAwz4hmKxhPOeLMIwZrLozsro5HTQhrsxw/viewform?usp=sf_link).


### Remove filter conditions

The filtering button is renamed "Filtered" and the icon is full when the collection is filtered.

![DataTable with filters conditions](/docs_images/getting-started/items/datablist-with-filters-ui-change.png#1364x213)

To remove a filter condition, open the filter modal, click the "trash can" button and submit with the **Apply** button.

![Remove a filter condition](/docs_images/getting-started/items/datablist-remove-filter-condition.png#1750x626)

### Filtering on built-in properties

Datablist comes with built-in properties (createdAt, updatedAt) which can be filtered as any other property. To be able to create filter conditions on your built-in properties, you must add them to your collection properties. [See our documentation on built-in properties](/docs/properties#built-in-properties).

### Filtering and data export

The export button in the [collection header](/docs/introduction#collection-header) exports the full collection items. To export only your filtered items, use the **Select all** checkbox and click the "Export items to CSV/Excel" button.

![Export filtered items](/docs_images/getting-started/items/datablist-export-filtered-items.png#1766x546)



## Delete items

To delete one or several items, select them with the left checkbox and use the **Delete items** top bar button.

> **Warning:** While it's possible to undo delete item operations while on the page, deleted items are **not** moved to trash but are permanently deleted. Please export your data before clearing a large amount of data.


Learn how to create new item and manage existing data in your Datablist collection.

Add, edit and delete items in Datablist

Add and manage items


Datablist has three ways to import data:
- [Using external files](#import-from-a-csv-or-excel-file)
- With [copy/pasting](#import-with-copypasting) from spreadsheet tools or tabular data
- Or using [Datablist API](https://developers.datablist.com)

## Import from a CSV or Excel file

Datablist is a great [CSV viewer and editor](/csv-editor). Use CSV and Excel files to import data into your collection. Select the collection where your data will be imported or [create a new collection](/docs/collections#create-a-collection) if needed.

![Import CSV/Excel file](/docs_images/import-export/datablist-import-csv-excel.png#1966x924)

On the first step, click the load zone to select a file from your computer, or drag and drop a file to get started. Both CSV and Excel files are accepted:
- CSV files must have a `.csv` file extension.
- Excel files must have one of the following file extensions: `.xlsx`, `.xls`, `.xlsm`, `.xlsb`, `.ods`.

> **Notes on importing an Excel file:**<br/>
> - Cells with formulas are imported with computed values
> - Empty rows are skipped. If headers are on the second row, it will work.

![Drag and Drop file](/docs_images/import-export/datablist-import-drag-and-drop.png#2177x1186)


### Create Properties on empty collection

When starting with an empty collection, the File Import assistant lists the columns from your file.

![Columns Import](/docs_images/import-export/datablist-import-create-properties.png#2126x1060)

Datablist analyses the data from your file to detect each column's data type. **Property types are guessed based on the first 100 items read on the file.** For example:

- Columns with valid emails (such as john.smith@example.com) are defined as **Email**
- Columns with full URLs (with HTTP, HTTPS or FTP protocol) are defined as **URLs**
- Columns with text longer than 70 characters are defined as **Long Text**
- Columns with valid [ISO 8601](https://en.wikipedia.org/wiki/ISO_8601) DateTime formats are defined as **DateTime**
- Columns with `Yes`, `No`, `1`, `0`, `True`, `False`, `Checked` are detected as **Checkboxes**
- Columns with valid numbers are detected as **Number**

To change the Data Type or to import column as another name, click the Data Type button.

![Edit Data Type](/docs_images/import-export/datablist-import-create-properties-edit.png#2126x1064)


### Map columns if collection has properties

On an existing collection with at least one property, you will be asked to map the file columns with your collection properties. When listing your file columns, Datablist will try to auto map the columns with existing collection properties.

> Notes: The auto-mapping algorithm works by removing all non-alphanumeric characters and comparing columns with property names in lower case

You can map one of your columns with the built-in **createdAt** property to set the items created timestamps. To do so, [add the built-in property to your collection](/docs/properties#built-in-properties). Then during the import process, map your file column to the property.

![Map Property](/docs_images/import-export/datablist-import-map.png#1928x1184)

If a column doesn't have a matching property, you can create new properties directly based on the file columns. To create a new property to match your file column, click the **+** button next to the property mapping select.

![Auto Create New Property](/docs_images/import-export/datablist-import-new-property.png#1296x372)

A modal will open to create a property. The name is set based on the column and a property type is suggested.


#### Property Settings

Property settings are accessible during the File Import process:

- Property name
- Property type
- **Do not allow duplicate values** - When one of your collection properties has a ["Unique Values option"](/docs/properties#ensure-unique-values-for-a-property), a **Merging Option** step will be shown. [Please check the bulk updates documentation page to know more.](/docs/bulk-update-data)

![New Property Settings](/docs_images/import-export/datablist-import-new-property-modal.png#1544x848)



### Converting to data types

After creating or mapping your columns, Datablist will parse and convert your lines according to the property data types.

- **Checkbox** - `Yes`, `No`, `1`, `0`, `True`, `False`, `Checked` (case insensitive) are converted to checkbox values
- **DateTime** - Must respect the [ISO 8601 format](https://en.wikipedia.org/wiki/ISO_8601). If not, data might be converted to some weird dates.
- **Number** - Numeric values must be written with numerical digits. Ex: `100` or `300.49` are valid, `one hundred` is **not** valid. **Decimal must use a dot separator.**

If imported data can't be converted to data type, data is passed as a Text. Review your data to detect any error and then click **Import items** to run the import process.

![Text to data types parsing](/docs_images/import-export/datablist-import-convertion.png#2118x1252)


### Run the import

Once ready, run the import to create the items. When the import is finished, a report is available with the number of items created.

![Import Report](/docs_images/import-export/datablist-import-complete.png#1554x888)


> **Note** <br />
> Loading a big CSV file takes time. Expect 5 minutes to load a 1 million lines CSV file. To cancel the loading process before the end, click the "Stop Import" button. It will stop the import process.


## Import with copy/pasting

To help you import data from any spreadsheet tools to Datablist, you can use copy/pasting. This feature allows you to import data from Google Sheets, Microsoft Excel, Apple Numbers, etc.

![Copy Google Sheets rows](/docs_images/import-export/datablist-copy-pasting-from-google-sheets.png#2022x1410)

In Datablist, select the collection where your data will be imported or [create a new collection](/docs/collections#create-a-collection) if needed. Then paste your data by selecting "Edit -> Paste" in your browser menu bar or using the **Ctrl + v** keyboard shortcut. A modal will open to configure the data import.

First, if your pasted data include headers/columns, set "**First row contains headers**" to true. The first row will be skipped and used to map or create properties.

![Paste on Datablist](/docs_images/import-export/datablist-import-copy-pasting.png#2230x1220)

If your collection has properties, map the columns with them. If you need to create new properties that match the columns, click the **+** button.

![Create a property](/docs_images/import-export/datablist-pasting-auto-property.png#1448x590)

When your pasted data contains headers, a property will be automatically created using your header name. [You will be able to edit it later.](/docs/properties#edit-or-delete-property)

For data without headers, clicking the **+** button will show an input to enter a property name.

![Create a property without header](/docs_images/import-export/datablist-paste-unknown-property.png#1682x740)

Once ready, click **Import** to run the import process.


> **Note:** Pasting data containing a single line will overwrite selected cell text


## Import Limits

Anonymous users have a 10,000 items import limit. [Create a free account](https://app.datablist.com/auth/signup) to remove the limit.

For registered users, import works with CSV and Excel files up to 1,5 million lines (1 million in [free plan](/pricing)).


Learn how to import data from Microsoft Excel or spreadsheet tools into your Datablist collection.

Importing Data into Datablist

Importing Data


**Unlike spreadsheet tools, it's easy to update your items with an external file in Datablist.** Thanks to data constraints, you can define a unique constraint on one of your properties so it acts as a unique identifier for your items.

## Define a unique identifier

To perform bulk updates, start with defining a unique identifier. Select one of your properties that must have unique values.

For example, on a people listing, email addresses or phone numbers are great as they are unique for each person. For companies listing, you can use their website URLs, etc. Any unique identifier is good.

Then, tell Datablist to use the property as a unique identifier by enabling the "Do not allow duplicate values" option. Open the [Manage Properties](/docs/properties#edit-or-delete-property) modal and [edit your property](/docs/properties#ensure-unique-values-for-a-property) so Datablist ensures it has unique values.

![Define Identifier](/docs_images/import-export/bulk-updates/datablist-bulk-update-create-identifier.png#1840x806)

Once your property is configured as unique, a **Key** symbol will appear in the property's column in the [Data Table](/docs/introduction#data-table).

![Check unique setting](/docs_images/import-export/bulk-updates/datablist-check-unique-property.png#1202x399)

### Remove duplicates

Configuring a property with a unique constraint ensures no duplicates can be added afterward but it doesn't ensure your existing items are unique.

To avoid any bad surprises, check for duplicates on your identifier.

Hopefully, Datablist provides a simple tool to find and merge duplicates. Click the "Duplicates" on your [collection header](/docs/introduction#datablist-layout).

![Duplicates Finder](/docs_images/import-export/bulk-updates/datablist-remove-duplicates.png#1016x325)

Then, choose "Selected Properties".

![Select your identifier property](/docs_images/import-export/bulk-updates/datablist-remove-duplicates-step1.png#1536x689)

And select your identifier property.

![Select your identifier property](/docs_images/import-export/bulk-updates/datablist-remove-duplicates-step2.png#1524x625)

👉 If duplicates are found, merge them.

## Bulk update items

Now you have a unique identifier property, simply import a CSV or Excel file containing a column to be matched with it. All file rows that match with collection items will update items and rows without matching items will create new items.

If your collection looks like:

```
 Name        | Email                
 John        | john@gmail.com       
 Frank       | frank@yahoo.com      
```

And Email is your unique identifier, you can upload a file to edit the Names, or to add new properties to your collection.

For example, importing a file with:

```
 Name            | Email                
 John Doe        | john@gmail.com       
 Frank Ciname    | frank@yahoo.com      
```

Will update the values of the property **Name**.

And importing a file with:

```
 Email                |   Company
 john@gmail.com       |   Google
 frank@yahoo.com      |   IBM
```

Will add a new property to your collection and add the company values to your existing items.

### Mapping identifier

When mapping your file columns with the collection properties, please check that a **Key** icon appears on your identifier column.

![Mapping](/docs_images/import-export/bulk-updates/datablist-bulk-upload-map.png#1466x844)


### Merging options

In the last step, you will be asked to select a merging option.

- **Skip** - If an item already exists with the same property, skip the file entry.
- **Soft Merge** - If an item exists with the same property, update empty item properties and don't update properties with data.
- **Hard Merge** - If data exists for the item property, update it.

![Merging Options](/docs_images/import-export/bulk-updates/all-merging-options.png#1752x1240)


> **Warning:** Always back up your data before performing any data operation.


Update your whole collection using and external file by defining a unique identifier for your collection.

Perform bulk updates using an external file (CSV or Excel)

Bulk update items


## Export data table

To download a file containing your data table items, simply click **Export** in your collection header.

> **Note:** Exported data represents your current data table items. If your collection is filtered -for example with a [search term](/docs/items#search-and-sort-items)- the export file will contain your filtered items.

![Export Button](/docs_images/import-export/export/datablist-export-button.png#1274x560)

A modal will open to select the Export format and the properties to export.

[CSV](/learn/csv/csv-uses) and Microsoft Excel (.xlsx) formats are available. When at least one of your properties is [hidden from the Data Table](/docs/properties#display-or-hide-properties-from-data-table), an option is shown to export only visible properties or all your properties.

For [CSV format](/learn/csv/csv-uses) exports, an option to select the column delimiter is available. **Comma** and **Semicolon** delimiters are available.

![Export Modal](/docs_images/import-export/export/datablist-export-modal-with-delimiter.png#1552x844)


You can open the generated file with Microsoft Excel, Google Sheets, Apple Numbers, or any [CSV editors](/csv-editor).

## Export selected items

To export only some items from your collection, [select items](/docs/items#select-items-and-top-bar) and click the "Export items to CSV/Excel" button in the top bar.

The export modal will open to perform an export with your selected items.

![Export Selected Items](/docs_images/import-export/export/datablist-selected-items.png#1569x875)

## Export with copy/pasting

Another simple way to export items or cells is to use copy/pasting. Select items or cells and click "Edit -> Copy" in your browser or use the keyword shortcut `Ctrl + c` to copy the data in your clipboard.

Clipboard data is compatible with any spreadsheet tools, [data editors](/data-editor), or text editors.

## Data Types export formats

When exporting data, Datablist converts all data types to string values:

- **Checkbox** data is exported with `TRUE` and `FALSE` values.
- **DateTime** data is exported using [ISO 8601 format](https://en.wikipedia.org/wiki/ISO_8601)


Learn how to export your data as CSV or Excel files in Datablist. Export all your collection items or only selected items.

Exporting your data

Exporting Data


Dealing with duplicates is an exhausting task with spreadsheet tools. Datablist provides a built-in deduplication feature to [find duplicate values](/features/duplicates-remover) in your collections. Duplicates can then be removed or merged (automatically or using a merging assistant).

To find the duplicates in a collection, click on the "[Duplicates Finder](/features/duplicates-remover)" button in your [collection header](/docs/introduction#collection-header).

![Duplicates Finder](/docs_images/data-management/find-duplicates/datablist-duplicates-finder.png#2444x1181)

## Select duplicate check method

The first step is to select how to compare items to find duplicate values. Two methods are available:

- **All Properties** - Look for items with similar values for all properties. Two items would be considered similar when all of their properties match.
- **Selected properties** - Select the properties to be used for similarity check. Two items would be considered similar when they have similar values on all the selected properties.

Most of the time, **Selected Properties** is the best option. This is perfect to [deduplicate contacts](/how-to/merge-duplicate-leads-without-losing-data) based on their email addresses and phone numbers, or companies using their website URLs. Use **Selected Properties** [when you have one or several properties that identify a product, person, company, etc.](/docs/properties#ensure-unique-values-for-a-property)

## Configure Properties

Next, if you click on the **Selected Properties** method, you have to select which properties will be checked.

For example, in a collection with people items, you would select the **Email** property.

![Example for Selected Properties](/docs_images/data-management/find-duplicates/datablist-select-properties.png#1356x518)


## Review and run duplicates check

Then, a review screen is shown with the number of items in your collection and the duplicate check mode selected. Click "Run duplicates check" to continue.

The duplicates analysis is a read-only operation. **It will not perform any changes in your collection items until you decide to merge items.**

> **Note:**<br />
> The algorithm to compare item values is **case insensitive**. For example, "JOHN@GMAIL.COM" and "john@gmail.com" will be duplicates.

![Example for Selected Properties](/docs_images/data-management/find-duplicates/datablist-duplicates-review.png#1342x566)


## Duplicates Listing

After running through all your items for duplicate items, Datablist will list all the duplicates found.

From this page, two actions are available:

- [Merge duplicates automatically without losing data](#automatically-merge-duplicates)
- [Merge conflicting items manually](#manually-merge-conflicting-items)

The recommended way to deal with duplicates is to run [auto merge duplicates](#automatically-merge-duplicates) first (**1** in the screenshot below) and then pursue with Datablist [merging assistant](#manually-merge-conflicting-items) for conflicting items (**2** in the screenshot below).

![Duplicate Item listing](/docs_images/data-management/find-duplicates/datablist-duplicates-listing.png#1502x1300)

### Automatically merge duplicates

To save you time, Datablist provides an "Auto Merge" algorithm. **With "Auto Merge", most of the merging cases are possible**. It handles [merging non-conflicting items](#merge-non-conflicting-items), [combining duplicate values into a single item](#combine-conflicting-properties), and [dropping duplicate values during the merging](#drop-conflicting-values). The auto merge is triggered by clicking on the "**Auto Merge duplicates when possible**" button.

The merging non-conflicting items algorithm is always activated. Other merging algorithms need to be switched on to be activated.

#### Merge non-conflicting items

Datablist is able to merge non-conflicting items automatically without losing any information. It works as follows:
- If all the duplicate items have the same property values, only one item will be kept and the others will be deleted.
- If the duplicate items are complementary, the item with the most information will be selected as the primary item and its property values will be filled using other item property values. Then all items except the primary item will be deleted.
- If duplicate items have conflicted property values, **items will be skipped for manual merging** (or to be combined with the [combining duplicates algorithm](#combine-conflicting-properties), or [dropped](#drop-conflicting-values))

For example, the following duplicates:

```
email            |     First Name   |    Last Name
james@gmail.com  |     James
james@gmail.com  |                  |     Bond
```

Will be merged into:

```
email            |     First Name   |    Last Name
james@gmail.com  |     James        |     Bond
```

#### Combine conflicting properties

The Auto Merge algorithm comes with a second option to combine values from duplicates into a single text property. It keeps the data from all the duplicate items and merges them with a delimiter into a single item.

One or more properties can be combined and 4 delimiters are available: `Line Break`, `Semicolon`, `Comma` and `Space`.

![Combine Duplicates - Options](/docs_images/data-management/find-duplicates/datablist-duplicates-auto-merge.png#1645x974)

For example, combining the **Phone** property with a **semi-colon**:

```
email            |       Phone       |     First Name   |    Last Name    
james@gmail.com  |  +33 1 34 65 23   |      James       |                 
james@gmail.com  |  06 13 42 78 23   |                  |     Bond        
```

Will be merged into:

```
email            |   Phone                         |     First Name   |    Last Name
james@gmail.com  |  +33 1 34 65 23;06 13 42 78 23  |     James        |     Bond    
```

This is useful when [merging a list of leads or companies](/how-to/merge-duplicate-leads-without-losing-data). If you have two leads with the same email address but different "Notes" and "Phone Number" values, combining them will create a consolidated lead.

> **Note**: **The algorithm only combines text values.** If the property you want to combine is a Checkbox, Number, Datetime, etc. (see full [data types list](/docs/properties#data-types)), it will **not** be combined.


#### Drop conflicting values

The last option available when merging duplicate items is to drop conflicting values.

Use this option:

- **When the property must be a single value.**
    - For example, if you are cleaning a CRM lead list. You will have an external CRM "record id". To re-import your cleaned data back into your CRM, the "record id" must be a single value.
- **When it doesn't make sense to keep several values.**
    - For example, if you have a "last activity" property with conflicting values. Date, Checkbox, and Number can't be combined so you can drop conflicting data to keep only one value.


> **Important**<br />
> Datablist selects one of the duplicate items to be a master item. When conflicts exist to merge items, the value from the master item is kept. **The item with the most properties containing data is selected as the master.**


For example, configuring the algorithm to drop conflicting values on AccountId:

```
AccountId        |       email          |     First Name   |    Last Name    |  Job Title
934DSFG39FGDS    |     james@gmail.com  |      James       |                 |
ODFJSDK123aSD    |     james@gmail.com  |                  |     Bond        |    CEO
```

Will be merged into:

```
AccountId        | email            |     First Name   |    Last Name    |  Job Title
ODFJSDK123aSD    | james@gmail.com  |     James        |     Bond        |     CEO
```

> **Algorithm Explanation**
> - The second item has 4 properties with data (`AccountId`, `email`, `Last Name`, `Job Title`). **It is the master item.**
> - `First Name`, `Last Name`, and `Job Title` are merged without conflict.
> - `AccountId` has a conflict. So the value from the master item is kept.


### Manually merge conflicting items

For some duplicate items, conflicting values prevent them to be merged without losing data. For example, imagine two items that store contact information with the following data:

```
# Contact A
Name: John Doe
Job Title: Marketing Manager
Email: johndoe@company.com
```

```
# Contact B
Name: John D.
Job Title: Business Development
Email: johndoe@company.com
```

We know they represent the same person because they have similar email addresses. Unfortunately, they have two different job titles, the name is not the same, and merging them into a single item means choosing which data to keep.

This is where to use Datablist Merging Assistant. A "merge" button is available on the left of every duplicates group.

![Manual Merging](/docs_images/data-management/find-duplicates/datablist-manual-merge.png#1874x301)

It opens the merging assistant for the items. On this modal, you can select which value to keep for each conflicting property. After merging them, all except one (the master item) will be deleted.

![Merging Assistant](/docs_images/data-management/find-duplicates/datablist-merging-assistant.png#1720x1050)

Please check our [Datablist Merging Assistant documentation page](/docs/merge-items) to learn more.


### Edit or delete items

Another way to deal with duplicate values is to directly edit an item's data or delete unnecessary items. You can directly perform those actions with the buttons listed on each item.

![Edit and delete buttons](/docs_images/data-management/find-duplicates/datablist-edit-delete-item.png#1781x302)


## To learn more

Read our guides for step by step tutorials on how to deal with duplicates for CSV and Excel files:

- [Merge duplicate rows in an Excel file](/how-to/excel-merge-duplicates)
- [Find and Merge CSV duplicates](/how-to/remove-csv-duplicates)


Dealing with duplicates is an exhausting task with spreadsheet tools. Learn how to find duplicate items in your collection and how to merge or remove the duplicates.

Find, remove or merge duplicates


Find and Replace is a powerful tool to clean data. When you need to replace a string in your data or to normalize values, Find and Replace is a perfect choice. And with the advanced options, it becomes a tool to remove strings from your texts.

Datablist offers a fast and powerful **Find And Replace** feature. Use it on any dataset size, from a few items to hundreds of thousands.

## Find and Replace workflow

### Step 1: Define the pattern and the options

From the [Datablist app](https://app.datablist.com), open the Find and Replace tool from the "Clean" menu.

![Open Find & Replace tool](/docs_images/data-cleaning/find-replace/clean-header-find-replace.png#1502x590)

The first step is to define the pattern to be looked for. And the property to search.

![Find and Replace inputs](/docs_images/data-cleaning/find-replace/find-replace-start.png#2356x1444)

The "Find" pattern is mandatory. All other inputs are optional. With an empty "Replace with" string, the pattern will be removed from your data.

Select if the search must be performed on a specific property or on all your data.

To learn more about the options, check the [Find and Replace Options](#find-and-replace-options) section.


### Step 2: Run the "find" phase

Datablist "Find and Replace" uses a two phases workflow. It first searches for all the occurrences of your entered pattern. And then, after your confirmation, it replaces them.

Click on the "Find" button to run the first phase.

![Search results](/docs_images/data-cleaning/find-replace/find-replace-preview.png#2278x1436)

On the search summary, you will find:

- How many occurrences of the pattern have been found
- How many distinct items have the pattern in their property(ies). If the pattern is found twice in a text, it will count for 1 item.
- The occurrences number per property.
- And a preview of the **replacement** process on a sample of 10 items.


### Step 3: Replace matched terms

At any moment, you can change the search options. Change the search pattern or the options until you get the requested preview results.

Then, run the replace phase by clicking "Replace All".

The replacement process is fast! On hundreds of thousands of items, it will take seconds or a few minutes. The more items to edit, the longer.

The items will be updated directly in the data table. Close the drawer or re-open the "Options" section to start a new Find and Replace process.

![Find & Replace results](/docs_images/data-cleaning/find-replace/find-replace-results.png#1534x852)


## Find and Replace Options

### Match case

By default, searching for "John" will return items that have "john", "John", or "JOHN" in their data. To make your search case-sensitive, and only replace items with "John", check the checkbox "Match case".

### Match using regular expression

When using regular expressions, all options except "Match case" are disabled. Please check the Find and Replace using [Regular Expression](#find-and-replace-using-regular-expression) to see examples.

![Find and Replace with Regular Expression option](/docs_images/data-cleaning/find-replace/find-replace-regex.png#1832x1022)

### Whole words

Searching for "and" will match "Land", "and", "Andor", etc. To only search for "and", check the "whole words" checkbox. This option can also be used with brackets or parenthesis. Search for `(s)` with "Whole words" checked to search and replace all `(s)` occurrences but not the ones belonging to words (like `street(s)`).


### Ignore Accents

Characters with accents are different from their non-accented ancestor. `é` is a different character than `e`, or `ë`. Datablist Find and Replace tool has the option to ignore the differences. Any accented or non-accented character will match any accented or non-accented character.

For example:

- Search for "Ile de R**é**" will match "Ile de Re", "Ile de Ré".
- Search for "Ile de R**e**" will also match "Ile de Re", "Ile de Ré".



## Find and Replace using Regular Expression

### Regular Expression Cheat Sheet

```
| ^  	| Start of string
| $  	| End of string
| \b 	| Word boundary
| \s 	| White space (tab, space, new line, etc.)
| \w 	| Word characters - A word character is a character a-z, A-Z, 0-9, including _ (underscore)
| \d 	| Matches digits from 0 to 9
| + 	| n+ - matches any string that contains at least one n
| * 	| n* - quantifier matches any string that contains zero or more occurrences of n
| ? 	| n? quantifier matches any string that contains zero or one occurrences of n
```

### Remove url scheme

```
^(http|https|ftp):?//(www)?(\.)?
```
And replace with an empty string.


![Remove URL scheme find](/docs_images/data-cleaning/find-replace/remove-url-scheme.png#2276x1442)

![Remove URL scheme preview](/docs_images/data-cleaning/find-replace/remove-url-scheme-results.png#2354x1452)


### Remove letter at the end

Define the letter you want to remove and add `$` to indicate the letter must be at the end.

Here is an example to remove the `/` from url.
```
/$
```

And replace with an empty string.

![Remove last letter](/docs_images/data-cleaning/find-replace/remove-end-letter-regex.png#1748x1464)

![Remove last letter preview](/docs_images/data-cleaning/find-replace/remove-end-letter-results.png#1742x1460)


### Get domain from an email address

```
^(\w)*@
```

And replace with an empty string.

![Get domain from email address](/docs_images/data-cleaning/find-replace/get-domain-email-regex.png#1832x1022)

![Get domain from email address preview](/docs_images/data-cleaning/find-replace/get-domain-email-results.png#1756x1456)


### Keep only the first word of a sentence (or keep the first name from full name)

```
^(?<first>(\w)*)(.*)
```

And replace with

```
$<first>
```

![Keep first word Regex](/docs_images/data-cleaning/find-replace/keep-first-word-regex.png#2276x1442)

![Keep first word results](/docs_images/data-cleaning/find-replace/keep-first-word-regex-results.png#1894x1460)


### Remove the first word of a sentence (or keep the last name from full name)

```
^(?<first>(\w)+)(\s)+(?<last>.+)
```

And replace with

```
$<last>
```

![Keep last name Regex](/docs_images/data-cleaning/find-replace/keep-last-name-regex.png#2176x1454)

![Keep last name results](/docs_images/data-cleaning/find-replace/keep-last-name-results.png#2154x1444)





## FAQ

### Why some properties are not available to search in?

Find and Replace is available only for Text and Number properties.



Finding and replacing text within a large data set is complex. Learn how to use Regex, and advanced options to clean your data.

Advanced Find and Replace

Find and Replace


Datablist's Merging Assistant helps you clean up duplicate items and merge them into one master item.

> **Notes:** To find and merge duplicate items, please check our [Find and remove duplicates](/docs/find-duplicates) documentation.

## Merging Assistant

The Merging Assistant is available directly in the top bar once you have at least two items selected ([see how to select items](/docs/items#select-items-and-top-bar)).

![Merging Assistant Button](/docs_images/data-management/merge-items/datablist-merging-assistant-button.png#1542x576)

Clicking on the button opens the **Merging Assistant** for the selected items.

Datablist analyses the items to find the one with the most data and defines it as the primary item. **The goal is to complete the primary item with data from "secondary items" to be able to delete those.**

![Merging Assistant](/docs_images/data-management/merge-items/datablist-merging-assistant.png#1730x1058)

Empty properties in the primary item are automatically filled with secondary item values if available. If several values compete for a property, clicking on a secondary item property's value copies its data into the primary item.

<div class="content-video">
    <video
        autoplay muted loop playsinline controls width="100%" height="auto" class="d-block">
            <source src="https://storage.googleapis.com/public_datablist/website/docs/data-management/datablist-merge-items.mp4" type="video/mp4" />
    </video>
    <div class="text-center">Merging Assistant</div>
</div>


Once done, clicking on "Merge" will delete all secondary items (if not set otherwise) and update the primary item accordingly.


Learn how to merge two or more items into a single consolidated item in Datablist. Merge contacts, leads or products with a no-code interface.

Merge two or more items into one consolidated item

Merge several items into one


Datablist provides an Undo / Redo functionality, which allows you to undo or redo changes to your collection, or items.

Undo and Redo actions can be triggered using keyboard shortcuts or with the "History" action in the [Collection Header](/docs/introduction#collection-header).

![History](/docs_images/productivity/datablist-history.png#1464x498)

## Undo

To undo a change, press Ctrl+Z (Windows) or Cmd+Z (Mac). Undo/Redo is currently available for the following changes:

- **Collection name** - Revert changes in the collection name
- **Collection icon** - Revert to previous collection icon
- **New item** - Delete newly created item
- **Item edit** - Revert your changes done through the [drawer](/docs/introduction#drawer) or the [Data Table](/docs/introduction#data-table)
- **Item delete** - Revert deletes for single items or bulk deletes
- **Column resize** - Revert column size changes in the [Data Table](/docs/introduction#data-table)

> **Warning:** Opening another collection clears history and prevents undoing previous changes


## Redo

If you need to redo an action, press Ctrl+Shift+Z (Windows) or Cmd+Shift+Z (Mac).


Learn how to undo any undesired change with Datablist Undo and Redo feature.

Undo and Redo user actions in Datablist

Undo and Redo


Learn how to use Datablist as quickly as possible with these keyboard shortcuts.

> **Note:** **Cmd/Ctrl** means **Ctrl** on Windows (or Chrome) OS and **Cmd (⌘)** on Mac OS


## General

- Open command bar with **Cmd/Ctrl + k**
- Use **n** to create a new empty collection
- Use **Cmd/Ctrl + z** to [undo an action](/docs/undo-redo)
- Use **Cmd/Ctrl + Shift + z** to [redo an action](/docs/undo-redo)
- Back or Close drawer/modal with **Esc**


<br/>


## On the DataTable

- Use **c** while on a collection's page to create a new item
- Use **Space** to open drawer for current item
- Use **Enter** to commit cell changes
- Use **Esc** to cancel cell changes in edit mode
- Use **Cmd/Ctrl** + **f** to search inside the collection
- Use **Cmd/Ctrl** + **c** to copy selected cells or items
- Use **Cmd/Ctrl** + **v** to paste data


<br/>

**Moving cursor**

- Move cursor right **→**
- Move cursor left **←**
- Move cursor up **↑**
- Move cursor down **↓**
- Use **Tab** to move to next cell (committing changes when pressed while editing)
- Use **Shift** + **Tab** to move to previous cell
- Move cursor to end of row with **Cmd/Ctrl** + **→**
- Move cursor to beginning of row with **Cmd/Ctrl** + **←**
- Move cursor to beginning of row with **Cmd/Ctrl** + **↑**
- Move cursor to end of items with **Cmd/Ctrl** + **↓**

<br/>

**Selecting Items**

- Use **Cmd/Ctrl** + **a** to select all items
- Use **Shift** and move up **↑** or down **↓** to select items
- Select an item checkbox and click on another item checkbox while pressing **Shift** to select all items in between


Learn how to use Datablist as quickly as possible with keyboard shortcuts.

Help Center

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