Microsoft offers the Azure Bot Service (replacing the former Microsoft Bot Framework), a managed bot building platform, which provides an integrated environment that is purpose-built for bot development, enabling you to build, connect, test, deploy, and manage intelligent bots, all from one place.
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Snowflake
Score 9.0 out of 10
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The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.
It is suited for applications like computerizing messages, or any business thought that would require the entrepreneur to robotize their reactions, particularly assuming they are managing a ton of clients and they can't answer to every single one of them. It'd be the most ideal to computerize messages of enormous associations where the reactions measure up to the clients' assumptions. It would be less appropriate in associations where clients' viewpoints matter and every client is interesting and requires the association's consideration, where the specialist organization doesn't need to sum up the clients' interests.
I am over our HR data, and we use Workday for our HR management system. I have a script in place that runs reports on Workday and saves the results as CSVs. I can then use stages in Snowflake to insert these CSVs into Snowflake, then I can insert or truncate and replace these staged tables into a final schema. Then once these are in a schema I can reference them and build out my data models. In addition to ingesting CSVs, Snowflake has the ability to write a CSV file to our Amazon S3 bucket. Ingesting these CSVs, transforming the data, then delivering it to a destination would've involved so much more coding than my current process if we were on any other platform.
Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
Snowflake manages concurrency better in our trials than other premium competitors
Snowflake has little to no setup and ramp up time
Snowflake offers online training for various employee types
They have simplified the coding for the bot in Azure, but it would help if the coding was further simplified so that non-IT can operate [and] create it easily.
This tool is very much technical and proper knowledge is required, so mostly you have to hire an IT team.
I wish if various videos could be available for basic quires like its initiation, then I think it would act as a guideline and would help the beginners a lot.
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
Azure Bot Service provides an integrated environment for bot development. Microsoft Azure Cloud is fully compatible and its security features. It's more important to pay attention to the logic of business than the specifics of each messenger. We don't have any issues using the bot framework because the implementation is excellent.
The interface is similar to other SQL query systems I've used and is fairly easy to use. My only complaint is the syntax issues. Another thing is that the error messages are not always the easiest thing to understand, especially when you incorporate temp tables. Some of that is to be expected with any new database.
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
Microsoft Bot Framework is much better and well more established without a lot of proprietary software/coding language. Lex is very limited with integration with standard hardware and network configurations. Lex has performance issues and was too slow to meet near real-time collaboration requirements. Bot Framework complements many other Microsoft communication products and this was key to implementing without a lot of new training required.
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system to store a large amount of data. All these functionalities give the better edge to Snowflake.
Interfaces with the SQL data set, tracks down plans/replies, and tests them with the SDK.
Utilizing the system is made conceivable by the Bot Dev gateway. We can interface our bot in excess of ten channels, including Twilio Facebook, Twilio, Twilio, and Slack, and that's only the tip of the iceberg.
Positive impact: we use Snowflake to track our subscription and payment charges, which we use for internal and investor reporting
Positive impact: 3 times faster query speed compared to Treasure Data means that answers to stakeholders can be delivered quicker by analysts
Positive impact: recommender systems now source their data from Snowflake rather than Spark clusters, improving development speed, and no longer require maintainence of Spark clusters.
