Key questions that were answered
Q1. What steps do we need to take to put a Data Culture in our Organization?
A Data Driven Culture starts from the top of an organization. The executive team champions the change. It is important that the organization starts measuring everything that can be quantified. The data from these measurements need to be retained and that’s really where the data warehouse comes in and then its important to provide self-service analytics which can be accomplished by providing access to Synapse analytics and Power BI and of course the Executive Team needs to communicate to the rest of the organization that this is the type of culture that they are trying to implement.
Q2. Our data warehouse solution currently helps us with the operational reporting. How do we embark on a project which would be a value add over our current set up? What is the journey you recommend undertaking so that we are able to reap the benefits of a cloud solution without putting too much burden on our current team and ecosystem?
We all know now that we can derive more intelligence and insights from our data. So, beyond operational reporting we can extend your current system, using the Azure Synapse, with impactful analytics to help you gain competitive advantage, without burdening your current setup.
Q3. Are there any prebuilt algorithms and tools available in Azure Synapse that would help us quickly reap the benefits of an Azure implementation quickly?
Yes. Azure Synapse comes Azure Machine Learning that has over 15+ algorithms in the areas of regression, classification, and clustering. These out of box algorithms help give a jump start to your analytics journey.
Q4. What are the advantages of Azure Synapse over other competing products like Snowflake and why should one pick Azure over them?
There are many worthy competitors in this field including offerings from Google, Amazon etc. but one recurring theme that keeps coming up as we speak with various clients, is that organizations that are already using Microsoft technologies, really prefer staying on the same stack, due to the familiar user experience and tight native integration offered between Power BI and Synapse, with the underlying Common Data Model, now called Dataverse. Other customers prefer an Azure Synapse solution because of its ability to reduce complexity, by bringing together all the needed elements for an end-to-end analytics solution, into one neat package, with market leading price/performance.
Q5. Can the Azure Data Lake and Azure Synapse take care of all our data warehousing needs?
Synapse analytics is designed from the ground up to work with structured, semi-structured and un-structured data so by using azure data lake and synapse analytics you can meet all your warehousing needs by using SQL OR Power BI against the Warehouse or by running spark by using different data lake or by using a different data language.
Q6. How much time does it take to implement Azure Synapse and what is the cost of implementing Azure Synapse Solution?
There is no one-size-fits-all answer here. The elements of the Azure Synapse service such as storage, SQL pools etc. are very much predictable and controllable. So, the costs really depend on the target variable, that we are trying to predict, and the effort needed to prepare your data. At a very high level, these projects could take anywhere between 3 to 6 months.