Amazon Redshift

We moved some of our data from Snowflake to Amazon Redshift which in our case saved us some money

Helped us with Business Intelligence

Provides as the compute engine for the data transformations, helping the analytics stack

Helps ML Products

Helped in achieving data consolidation that enables business to make data based decisions

Saved engineering cost with easy to set ETL processes

Greater ROI, as it is 1/10th the cost of traditional data stores and data warehouses.

it is connected to Tableau and Looker dashboards, and various reporting used by Sales, Marketing, Publishers, Operations, BI, Analytics, DataScience, Finance

Redshift is comparatively cheap and only charges for the time you actually use it

The insights gained from Redshift helps improve the business for the company

The stakeholders love it for being quick with all the processing

Without Amazon Redshift, we were not be able to build our data warehouse and provide the foundation to our BI module.

I don't see any negative impact except the costs that we have now.

Redshift as a solution is viable in case an enterprise wants a relatively uncomplicated relational data storage engine that is elastic and autonomous.

The costs are reasonable compared to other storage systems provided Redshift is capable to grow with your business and reduce administrative costs.

Redshift integrates well with many of the offerings within AWS and outside it. The programmability story is also good.

Lightning speed

Business is keen to use cloud-based products

Due diligence required for initial (migration) phase

Redshift leapfrogged Hive, providing a more stable, standardized, and scalable solution for querying server logs and raw usage data. This simplified data infrastructure while improving usability for users who are not on engineering staff as well as for power users.

In our case Redshift is much cheaper than other solutions

Faster than MySQL

Better aggregation

Expensive

It helped us in providing the data lake solution.

It has fast implementation speed so we can easily do sandboxing.

It supports lots of other tools so ETL is easy.

High Price : makes ROI tougher

Best for DW in our POC

Economically it made a lot of sense for us to jump into this.

Replication was a breeze.

Constant killed queries.

Not much performance boost in terms of the cache.

Users perceived the data warehouses as incapable of supporting widespread usage throughout the enterprise.

Cheaper cost to run.

Readily available and can easily expand.

Part of the AWS echo system which is great, because our Analytic tools are also part of AWS.

As of now, there are no results on the ROI, as we have just deployed this tool about a year ago. But this is a good tool to use as it is the advanced version of the data reporting platform.

With the help of Amazon RedShift, we can properly use our server spaces which in result gives a proper ROI as with the limited storage capacity we can store enough data.

It tends to work very slow, so it reduces the efficiency of the employees who are using it. Hence this is the major challenge with the employees.

Realtime and high availability, add quick access of the data.

Improve decision support based on quick data analytics.

Costlier compared to others, but we can generate ROI within a year, based on large scale applications.

I have not found any negative impact.

Very positive for what it has done, providing a way to aggregate data sources.

It allows marketing to pull statistics across the consumer base that would not have been otherwise possible.

It allows actual analytics across the company, in an easily accessible manner.

Easy to set up and very cost effective to run large complex queries.

Separation of roles between our production and analytic environment.

A lot of cloud service is RedShift ready (i.e., Segment, FiveTran, Matillion) which decreases implementation efforts

As long as you have the perfect designer and architect, you will receive the expected benefit from Amazon Redshift.

A client was unhappy and complained about slowness. Once we explained and showed them the new tool, they became very happy and stayed.

A faster and easy approach to OLAP Schema allowed us to think out of the box.

It allows for an almost seamless integration of our data which can then be used by other departments for analytical purposes.

No in house resources are needed for keeping the data alive and performing backup/migration tasks of the data in its end state.