corrected docs

docs/configurations/adoption_versions_comparsion.md

@@ -11,7 +11,7 @@ Please find the difference in the changes with different version, latest three v
 | stats table schema changes | refer rule table creation [here](https://glowing-umbrella-j8jnolr.pages.github.io/0.7.0/getting-started/setup/) | added additional columns <br> 1. `source_query_dq_results` <br> 2. `final_query_dq_results` <br> 3. `row_dq_res_summary` <br> 4. `dq_run_time` <br> 5. `dq_rules` <br><br> renamed columns <br> 1. `runtime` to `meta_dq_run_time` <br> 2. `run_date` to `meta_dq_run_date` <br> 3. `run_id` to `meta_dq_run_id` <br><br> documentation found [here](https://glowing-umbrella-j8jnolr.pages.github.io/0.7.0/getting-started/setup/)| remains same | 
 | stats table creation required | yes | yes - creation not required if you're upgrading from old version but schema changes required | automated |
 | notification config setting | define global notification param, register as env variable and place in the `__init__.py` file for multiple usage, [example](https://glowing-umbrella-j8jnolr.pages.github.io/0.7.0/examples/) | Define a global notification parameter in the `__init__.py` file to be used in multiple instances where the spark_conf parameter needs to be passed within the with_expectations function. [example](https://glowing-umbrella-j8jnolr.pages.github.io/0.7.0/examples/) | remains same |
-| secret store and kafka/ nsp authentication details | not applicable | not applicable | Create a dictionary that contains your secret configuration values and register in `__init__.py` for multiple usage, [example](https://glowing-umbrella-j8jnolr.pages.github.io/0.8.0/examples/) |
+| secret store and kafka authentication details | not applicable | not applicable | Create a dictionary that contains your secret configuration values and register in `__init__.py` for multiple usage, [example](https://glowing-umbrella-j8jnolr.pages.github.io/0.8.0/examples/) |
 | spark expectations initialisation | create SparkExpectations class object using the `SparkExpectations` library and by passing the `product_id` | create spark expectations class object using `SpakrExpectations` by passing `product_id` and optional parameter `debugger` [example](https://glowing-umbrella-j8jnolr.pages.github.io/0.7.0/examples/) | create spark expectations class object using `SpakrExpectations` by passing `product_id` and additional optional parameter `debugger`, `stats_streaming_options` [example](https://glowing-umbrella-j8jnolr.pages.github.io/0.8.0/examples/) |
 | spark expectations decorator | The decorator allows for configuration by passing individual parameters to each decorator. However, registering a DataFrame view within a decorated function is not supported for implementations of query_dq [example](https://glowing-umbrella-j8jnolr.pages.github.io/0.7.0/examples/) | The decorator allows configurations to be logically grouped through a dictionary passed as a parameter to the decorator. Additionally, registering a DataFrame view within a decorated function is supported for implementations of query_dq. [example](https://glowing-umbrella-j8jnolr.pages.github.io/0.7.0/examples/) | remains same |