How to save your work and pick it up again later

01Why saving needs a plan

An analysis is more than its final tables. It includes the dataset after cleaning, the labels you added so that variables are readable, the codes you applied to interview text, and the sequence of steps that produced each result. If any of these is lost, you cannot easily repeat the work, and you cannot show a reviewer how a number was reached.

Two habits protect against this. The first is to keep the original data untouched. Whatever you do in an analysis tool, the file you collected should stay exactly as it was, so you can always start again. The second is to save the working state at points that matter, such as after cleaning is finished and again before a report is written. A saved state is a record of what you did, and it lets you stop and resume without repeating hours of preparation.

02What a session contains

In AnalyZ Solutions, everything you are working on in a visit is called a session. A session holds your dataset, the variable and value labels you defined, your codes and coded themes, and the history of the changes you made.

The default is that a session lives only in your browser's memory. This is how the privacy model keeps your data off any server, and it means that closing the tab ends the session. That is safe, but it also means unsaved work is gone. There are two ways to keep it, and they are meant for different needs.

03The three options compared

04Option one: local saving

Local saving is a switch in the sidebar. When it is on, AnalyZ Solutions keeps a working copy of your session in your browser's own storage, on your device. If you close the tab and open AnalyZ Solutions again in the same browser, your session is there. After 24 hours the copy is removed automatically.

It is a convenience for short breaks and unexpected crashes, not a place to keep a project. It is tied to one browser on one device. Clearing your browser's site data, switching browsers, or using a private window means the copy is not there. It is also off by default, so you choose whether a copy of your data stays on a device. On a shared or public computer, leave it off.

05Option two: save a session file

A session file is the durable option. It saves your whole session as one file ending in .analyz.json. You choose where it goes, and you can reopen it at any time to restore your data, labels, codes and history exactly as you left them.

1. Finish a stage of work
   Save after a stage that took effort, such as cleaning the data or finishing a round of coding, rather than only at the end.
2. Save the session
   Use the save option in the sidebar. Your browser downloads the file.
3. Name it so you can find it later
   Include the project and the date, for example household-survey-cleaned-2026-10-07.analyz.json. A new file for each major stage gives you a trail you can go back along.
4. Store it with the same care as the data
   The file contains your data. Keep it in the same protected place as the original, and do not email it or upload it to a public folder if the data is sensitive.
5. Restore it when you return
   Load the session file the same way you load a dataset, and your work comes back as it was.

06What is not saved

• Access tokens. If your data came from a connection to KoBo, ODK, REDCap or Google Sheets, the connection settings are saved but the token is not. You are asked for it again when you refresh. A file that can be shared should never carry a password.
• The original file. A session records the state of your working copy. It does not replace the file you collected, which you should keep separately.
• Published links. Publishing a dashboard or a Data Canvas story creates a separate shared copy. That is a different action from saving your session.

07Saving dashboards and stories

You can save a dashboard or a Data Canvas story privately on any plan, including the free plan, without making it public. Publishing as a public link is a separate step available on the Starter and Pro plans. If you only need to continue working later, saving privately is enough. See how to build charts and share a dashboard and how to tell a story using your data for the sharing options.

08A routine that works

• Keep the original data file, unchanged, in its own folder.
• Load it, and run a data quality audit before you change anything.
• Clean and label the data, then save a session file. This is your cleaned baseline.
• Do your analysis and coding, saving a new dated file after each major stage.
• Turn local saving on for days when you will be interrupted, and off on shared computers.
• Before you write up, save a final session file next to the report, so the numbers can be traced.

If you do qualitative work, saving matters even more. Your thematic codes are part of the session, so a session file is also the backup of your codebook and coded segments.