Azure Analysis Services vs. Azure Data Lake Analytics

Microsoft Azure Analysis Services is best tool which is well suited for many type of scenarios. Like if the organization is dealing with a lot of critical data and need some better analysis and insights for that data then tool serves the best. It helps in depth analysis and getting the desired result which helps in making big decision for any organization. We can create role based access for sensitive data hence it is very helpful for security point of view. Helps in making the business more productive and taking decision based on facts. It is less appropriate for scenarios like where data amount is less and the solution is very costly and someone can get a cheaper solution. Also not suited for environment where user directory do not exist because without the help of user directory role could not be created hence proper utilization of this tool will not be possible.

Incentivized

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

• You can import data from various sources (i.e. Oracle, Azure SQL...)
• You can store data models
• You can elaborate data and create insights
• Perfect integration with Excel and Power BI

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

• Microsoft Azure Analysis Services is very costly solution and in that price we can get some better business intelligence tool with lot more of capabilities
• The dashboard or we can say user interface is complex and need time to understand and gain expertise in order for proper working.
• It needs continuation monitoring which is sometime a big task.
• Sometime, the tool shows unusual behavior and become unstable, so we need to clear temp files for proper functioning.

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

We have used the IBM cloud which was truly a specific nightmare for our team. User experience, layout, and design is big for us as it understandably is with many people. Even if any type of program can technically do all that we need it to, we still found our team will not be as motivated or satisfied using it compared to something more visually appealing and smooth.

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

• Website analytics; We have realized so many benefits like traffic analysis, CRM, click-through funnels, and many more.
• Aas allows us to do complex calculations and aggregations at slight efforts. It accommodates DAX expression, which in return is simple to apply.

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