Take a look at these new features – they should bring a smile to your face.

Data editing

Data Table block in the workflow, linked to the improved Table View in the Report, empowers project editors and report viewers to snapshot, query and edit data, to amend mistakes or add comments and push the edited data ‘upstream’ into the workflow. Read more

Data validation

Validate data block can automate multiple data quality scans, such as data schema and values. Create alerts should something fail the criteria or add an output with diagnostics report, telling you about everything that failed, so you can quickly identify the problems. More..

Data alerts

Email block makes communication an integral part of the data management process: notify the report viewer that their report is ready, or let the analyst know they need to fix something, by sending them those validation diagnostics.

Before you ask – email output is integrated with the Batch output block, so you can use it in the multi-user publishing scenarios. More…

Block bookmarks

Bookmark frequently used workflow blocks to avoid having to configure them repeatedly – works for the multi-tab Reports and coding blocks too!
Find more here

Salesforce integration

The Salesforce connector is now added to Evo, making it easy to integrate SF API with data coming from other sources to create a complete overview of your business, edit the CRM data, even publish it back to Salesforce, should you wish to.  Read more

Finally – we’ve added some features to make the report formatting easier.

As usual, make sure to check our changelog to see features making their way daily.

Stay tuned, stay safe and let us know if you have any feedback

#TeamVisokio

The post Rocking after Rock – new Omniscope features appeared first on Visokio.

Editing + Workflow Execution

Attached here you’ll find a IOZ file to import the project locally to play with 2 interesting features:

1. 1. Edit data from a Report using the “Editable Table” view.  When connected to a Text Input or Data Table block the view allows you to perform data edits as if it was a simple spreadsheet app.
   2. Execute specific blocks of a Workflow through a Custom view in the Report app which uses the Workflow REST API

A simple custom view to control Workflow Execution from the Report has been added to our GitHub repo, you’ll find it in your Omniscope Evo by clicking on the Add View menu (alt+A) -> and selecting or typing “Workflow Execution”

A video which describes the project is available here. Enjoy.

The post How to Edit data and Execute Workflow from Report appeared first on Visokio.

This is something we have done to help measuring air pollution in Puglia (Italy), but you can apply this concept to anything. For instance you might want to Tweet financial news when data meets a certain threshold, or tweet an update on your company page when a new feature is released.

Step by step, here is described how we built and power this Twitter Omniscope data alerts bot – @OmniscopeBot.

An example tweet:

Omniscope data alerts bot on Twitter

Air pollution alert – https://t.co/5TcJZ0Vhv8 – daily average over limit: * Brindisi – Via dei Mille, PM10: 82.47 µg/m³;

1. Setup your Twitter developer account and create your app

To build your bot the first thing to do is to apply for a Twitter developer account on developer.twitter.com .

You can build your profile for personal use or for your organisation, either ways Twitter needs to know what’s the reason for the developer account, so you have to specify the details to get approved, making sure to be thourough in the explaination.

Once your account is verified you can create your Twitter app, which it will be in practice used by your bot to tweet.

The main things to obtain once you have created your Twitter app are: the API keys and access tokens. They allow a script (e.g. a Python script) to communicate with your Twitter app.
On the Twitter app page, go to the App details to obtain the 4 keys and tokens. N.B. anyone with these keys will be able to access your account, keep them safe!

2. Setup the data workflow

In our case the workflow is obtaining data from a remote service, so we are pulling data in Omniscope, cleaning, transforming, and then we have a path to validate the data: any measurement above limit will be gathered, ready to be used to compose the text to tweet.

This is the resulted workflow:

Arpa Puglia Monitor

No Description

The bottom right part (highlighted in yellow) is the one which aggregates the data to evaluate a sum, to then compare the measurements against the limits.
If some rows are produced by the record filter block (the data over the limits, signifying anomalies) the information is sorted and passed to the Python – Twitter block, where the tweeting happens.

3. Setup the Python to post updates / alerts

To tweet we use a very common Python library https://pypi.org/project/python-twitter/ , which allows you to authenticate to your account through the API keys and tokens, post updates to your account and more.

This is the content of the Custom Python block in Omniscope which gets the input data, builds a message and tweets on the bot account.

import twitter, sys

if len(input_data) <= 0:
sys.exit(2)

#Omniscope Bot
api = twitter.Api(consumer_key="xxx",
consumer_secret="xxx",
access_token_key="xxx-xxx",
access_token_secret="xxxx")

message="Air pollution alert - https://bit.ly/ArpaPuglia24h - daily average over limit: "

for index, row in input_data.iterrows():
message+= " \n• "+ row['Centralina'] + ", " + row['Inquinante'] + ": " + str(row['Media giornaliera']) + " "+ row['Unita Misura']+";"

try:
status = api.PostUpdates(message)
except UnicodeDecodeError:
print("Your message could not be encoded. Perhaps it contains non-ASCII characters? ")
print("Try explicitly specifying the encoding with the --encoding flag")
sys.exit(2)

output_data = pandas.DataFrame([message])


Note that the consumer_key, consumer_secret, access_token_key, access_token_secret have been obscured, and those are the only bits you have to customise to allow the script communicating with your Twitter app.

The PostUpdates method is the one which posts a tweet on your page. In this case we are concatenating rows from the input data to build a message showing all measurements which are above a certain limit.

4. Automate the workflow

The last step obviously is to automate the workflow, to run at certain time / interval. This is done by setting up a Omniscope Scheduler task which re-execute the whole workflow to get new data, validate the information and tweet in case of anomalies.

Enjoy!

The post How to build a Twitter bot posting data alerts appeared first on Visokio.