term: review usage of "colleague" and "team".

pages/features.js

@@ -63,7 +63,7 @@ export default () => (
               alt="Reproducibility"
             />
           </Icon>
-          <Name>Reproducible </Name>
+          <Name>Reproducible</Name>
           <Description>
             The single 'dvc repro' command reproduces experiments end-to-end.
             DVC guarantees reproducibility by consistently maintaining a
@@ -78,7 +78,7 @@ export default () => (
               alt="Low-friction branching"
             />
           </Icon>
-          <Name>Low friction branching </Name>
+          <Name>Low friction branching</Name>
           <Description>
             DVC fully supports instantaneous Git branching, even with large
             files. Branches beautifully reflect the non-linear structure and
@@ -92,7 +92,7 @@ export default () => (
           <Icon>
             <img src="/static/img/features/icons/storage-icon.svg" alt="" />
           </Icon>
-          <Name>Metric tracking </Name>
+          <Name>Metric tracking</Name>
           <Description>
             Metrics are first-class citizens in DVC. DVC includes a command to
             list all branches, along with metric values, to track the progress
@@ -154,8 +154,8 @@ export default () => (
           </Icon>
           <Name>Track failures</Name>
           <Description>
-            Bad ideas can sometimes bring more information to colleagues than
-            the successful ones. Retaining knowledge of failed attempts can save
+            Bad ideas can sometimes spark more information among colleagues than
+            successful ones. Retaining knowledge of failed attempts can save
             time in the future. DVC is built to track everything in a
             reproducible and easily accessible way.
           </Description>

src/UseCases/index.js

@@ -35,10 +35,10 @@ const Heading3 = () => (
 
 const Description1 = () => (
   <Description>
-    At any time, fetch the full context about any experiment you or your team
-    has run. DVC guarantees that all files and metrics will be consistent and in
-    the right place to reproduce the experiment or use it as a baseline for a
-    new iteration.
+    At any time, fetch the full context about any experiment you or your
+    colleagues have run. DVC guarantees that all files and metrics will be
+    consistent and in the right place to reproduce the experiment or use it as a
+    baseline for a new iteration.
   </Description>
 )
 

static/docs/get-started/reproduce.md

@@ -11,8 +11,8 @@ If you just cloned the
 [project](https://github.com/iterative/example-get-started), make sure you first
 fetch the input data from DVC by calling `dvc pull`.
 
-It's now extremely easy for you or anyone in your team to reproduce the result
-end-to-end:
+It's now extremely easy for you or any colleague in your team to reproduce the
+result end-to-end:
 
 ```dvc
 $ dvc repro train.dvc

static/docs/get-started/store-data.md

@@ -9,8 +9,8 @@ $ dvc push
 ```
 
 The same way as with Git remote, it ensures that your data files and your models
-are safely stored remotely and are shareable. It means that this data could be
-pulled by your team or you when you need it.
+are safely stored remotely and are shareable. This means that the data can be
+pulled by yourself or your colleagues whenever you need it.
 
 Usually, you run it along with `git commit` and `git push` to save the changed
 [DVC-files](/doc/user-guide/dvc-file-format).

static/docs/tutorial/sharing-data.md

@@ -47,8 +47,8 @@ pushed because the rest of the data files belong to different branches like
 
 ## Pulling data from the cloud
 
-In order to reuse your data files, a colleague of yours can pull data the same
-way from the master branch:
+In order to reuse your data files, a colleague can pull data the same way from
+the master branch:
 
 ```dvc
 $ git clone https://github.com/dmpetrov/new_tag_classifier.git

static/docs/understanding-dvc/how-it-works.md

@@ -72,14 +72,14 @@
        Rscript plot.R result.csv plots.jpg
    ```
 
-7. The cache of a DVC project can be shared with your colleagues and partners
-   through Amazon S3, Azure Blob Storage GCP Storage, among others:
+7. The cache of a DVC project can be shared with colleagues through Amazon S3,
+   Azure Blob Storage, GCP Storage, among others:
 
    ```dvc
    $ git push
    $ dvc push # push from the cache to remote storage
 
-   # On a colleague machine:
+   # On a colleague's machine:
    $ git clone https://github.com/dataversioncontrol/myrepo.git
    $ cd myrepo
    $ git pull # download tracked data from remote storage

static/docs/use-cases/shared-development-server.md

@@ -6,10 +6,10 @@ such as ability to use multiple GPUs, store all your data in one place, etc.
 
 ![](/static/img/shared-server.png)
 
-With DVC, you can easily setup a shared data storage on the server that will
-allow your team to store and share data for your projects effectively, as well
-as to have an instantaneous <abbr>workspace</abbr> restoration/switching speed –
-similar to `git checkout` for your code.
+With DVC, you can easily setup shared data storage on the server. This allows
+your team to store and share data for your projects effectively, and to have an
+instantaneous <abbr>workspace</abbr> restoration/switching speed – similar to
+`git checkout` for your code.
 
 ### Preparation
 
@@ -22,7 +22,7 @@ $ mkdir -p /path/to/dvc-cache
 ```
 
 You will have to make sure that the directory has proper permissions setup, so
-that every one on your team can read and write to it and can access cache files
+that all your colleagues can read and write to it and can access cache files
 written by others. The most straightforward way to do that is to make sure that
 you and your colleagues are members of the same group (e.g. `users`) and that
 your shared cache directory is owned by that group and has respective
@@ -58,9 +58,9 @@ $ git commit -m "dvc: shared external cache dir"
 
 ### Examples
 
-You and your colleagues can work in your own <abbr>workspaces</abbr> as usual
-and DVC will handle all your data in the most effective way possible. Let's say
-you are cleaning up the data:
+You and your colleagues can work in your own separate <abbr>workspaces</abbr> as
+usual, and DVC will handle all your data in the most effective way possible.
+Let's say you are cleaning up the data:
 
 ```dvc
 $ dvc add raw
@@ -70,9 +70,9 @@ $ git commit -m "cleanup raw data"
 $ git push
 ```
 
-Your colleagues can pull the code and have both `raw` and `clean` instantly
-appear in their workspace without copying anything. After this they decide to
-continue building this pipeline and process the cleaned up data:
+Your colleagues can pull the code and have both `raw` and `clean` data files
+instantly appear in their workspace without copying anything. After this they
+decide to continue building this pipeline and process the cleaned up data:
 
 ```dvc
 $ git pull

static/docs/user-guide/contributing.md

@@ -158,9 +158,9 @@ variables, use:
 $ source tests/remotes_env
 ```
 
-If another member of your team has already gone through this guide, you could
-just ask for their `remotes_env` file and Google Cloud credentials, and skip any
-env manipulations below.
+If one of your colleagues has already gone through this guide, you could just
+ask for their `remotes_env` file and Google Cloud credentials, and skip any env
+manipulations below.
 
 <details>