Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on data—the serverless integration service does the rest.
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Looker
Score 8.4 out of 10
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Looker is a BI application with an analytics-oriented application server that sits on top of relational data stores. It includes an end-user interface for exploring data, a reusable development paradigm for data discovery, and an API for supporting data in other systems.
Well-suited Scenarios for Azure Data Factory (ADF): When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources. Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing. For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy. Less Appropriate Scenarios for Azure Data Factory: Real-time Data Streaming - Azure Data Factory is primarily batch-oriented. Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice. Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.
When data drives potential for new orders, Looker earns its place in our tech stack. If, on the other hand, we are hoping for pipeline generation, Looker is useful if you are willing to repeatedly go check customer utilizations .... it is not appropriate if you are hoping to automate data analysis for this purpose.
It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
We can use linked service in multiple pipeline/data load.
It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.
Show visited pages - sessions, pageviews - which programs are viewed the most.
Displays session source/medium views to see where users are coming from.
It shows the video titles, URLs, and event counts so we can monitor the performance of our videos.
It gives a graphic face to the numbers, such as using bar charts, pie graphs, and other charts to show user trends or which channels are driving engagement.
Our clients like to see the top pages visited for a month.
I like the drop-and-drag approach, and building charts is a little easier than it was before.
I give it this rating because it deems as effective, I am able to complete majority of my tasks using this app. It is very helpful when analyzing the data provided and shown in the app and it's just overall a great app for Operational use, despite the small hiccups it has (live data).
So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.
Looker is relatively easy to use, even as it is set up. The customers for the front-end only have issues with the initial setup for looker ml creations. Other "looks" are relatively easy to set up, depending on the ETL and the data which is coming into Looker on a regular basis.
Somehow resources heavy, both on server and client. I recommned at least 50Mbs data rate and high performance desktop comouter to be abke to run comolex tasks and configure larger amount of data. On the other hand, the client does not need to worry when viewing, the performance is usually ok
We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue
Never had to work with support for issues. Any questions we had, they would respond promptly and clearly. The one-time setup was easy, by reading documentation. If the feature is not supported, they will add a feature request. In this case, LDAP support was requested over OKTA. They are looking into it.
The easy integration with other Microsoft software as well as high processing speed, very flexible cost, and high level of security of Microsoft Azure products and services stack up against other similar products.
Looker Studio, you can easily report on data from various sources without programming. Looker Studio is available at no charge for creators and report viewers. Enterprise customers who upgrade to Looker Studio Pro will receive support and expanded administrative features, including team content management. So it's good.
Looker has a poignant impact on our business's ROI objectives. As an advertising exchange we have specific goals for daily requests and fill, and having premade Looks to monitor this is an integral piece of our operational capability
To facilitate an efficient monthly billing cycle in our organization, Looker is essential to track estimated revenue and impression delivery by publisher. Without the Looks we have set up, we would spend considerably more time and effort segmenting revenue by vertical.
Looker's unique value proposition is making analytical tools more digestible to people without conventional analytical experience. Other competing tools like Tableau require considerably more training and context to successfully use, and the ability to easily plot different visualizations is one of its greatest selling points.