Azure Data Lake Analytics vs. Hashboard (discontinued)

For us we have an enterprise of SQL users at all skill levels, and this product is very SQL friendly and extremely fast in creation of data aggregates and analysis. If you are an Azure storage user, considering using Lake Analytics over top of your blob or any other storage just adds complementary services and functions native to your existing architecture.

Incentivized

For the scenario, we used Glean.io which we used the software to establish a database connection and build live dashboards on the data on this database. This was a very simple use case to explore the capabilities of the software. In this use case, it works very smoothly and well. Further, we looked into similar use cases using the data ops features to achieve data provisioning with code to have more control. This was a nice way to support data engineers for sure. I would say that - for our use cases - the UI-based set up does the job. It is nice to have more advanced options with data ops. But they are probably over the top for our use cases. I would say it is worth it though to explore and figure out which degree of control fits your use case best.

Incentivized

• It combines big data.
• Monitors and alerts are helpful.
• Report visualization relies on analytics.
• It is compatible with Power BI services for report generation.

Incentivized

• Workflow is easy and clear due to clean and state of the art interface
• Model creation is easy
• Possibility for custom SQL code for database connection is very helpful

Incentivized

• There's a bit of bias towards cloud with ADL Analytics. Depending upon a company's infra strategy and investment plans, there are some challenges with migration and integeration.
• Not worth the time/effort/money if the organization doesn't have "Volume" of data. Cost effective only when daily loads exceed around 1million.
• While training materials are available online, Adoption rate - Yet to pick up.

Incentivized

• Querying has to be done by users only. There can be ways to automate querying using templates
• Not able to clearly check the query run time
• The customer support team can be little more proactive while communicating any changes and resolving any queries

Incentivized

Azure Data Lake simplifies extensive data analysis. It runs Hadoop, HDInsight, and Data Lakes, and even complex queries run smoothly and quickly. We write queries to transform data and extract insights instead of configuring hardware. It can handle any size job by adjusting the power. Azure's servers, networking, and data entry are fantastic. It provides security and assured data access.

Incentivized

Glean.io provided the customisable packages as per the user licences and data storage required. We are a growing organisation and this flexibility helped arrive at decision to use Glean.io The user onboarding is very easy with Glean.io. There were no extra resources required to integrate with our system and it was done in couple of days only.

Incentivized

• Since we have implemented this solution, we have been more able to follow what is going on in our process and sells.
• We are also sparing some money by comparing the costs now against the costs we had on-premise.

Incentivized

• Optimised the DB management team by 30%
• Reduce in data visualisation dashboards TAT by 50%
• Increase in revenues and savings by 20%

Incentivized