If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for)
SAS Advanced Analytics excels with projects that have at least 3 parts. The first part is the ability to address and compare different modeling types. Suppose you are an analyst interested in predicting home prices or whether an individual will reapply for unemployment insurance. There are lots of model types that could work for these two situations. SAS Advanced Analytics makes it easy (although not as easy as SAS Enterprise Miner) to compare the performance of different modeling types, such as comparing support vector machines with random forest models. A second scenario that SAS Advanced Analytics does a good job at is making the analysis reproducible. By showing the lineage of analyses, another analyst is able to follow the work of the previous analyst. This is a huge advantage for individuals working in corporations or governments. The third area SAS Advanced Analytics is useful is in text analytics. The field is huge now, and I haven't come across a software that makes text analytics as easy as SAS Advanced Analytics.
[Amazon] Redshift has Distribution Keys. If you correctly define them on your tables, it improves Query performance. For instance, we can define Mapping/Meta-data tables with Distribution-All Key, so that it gets replicated across all the nodes, for fast joins and fast query results.
[Amazon] Redshift has Sort Keys. If you correctly define them on your tables along with above Distribution Keys, it further improves your Query performance. It also has Composite Sort Keys and Interleaved Sort Keys, to support various use cases
[Amazon] Redshift is forked out of PostgreSQL DB, and then AWS added "MPP" (Massively Parallel Processing) and "Column Oriented" concepts to it, to make it a powerful data store.
[Amazon] Redshift has "Analyze" operation that could be performed on tables, which will update the stats of the table in leader node. This is sort of a ledger about which data is stored in which node and which partition with in a node. Up to date stats improves Query performance.
Complex Survey Analysis- SAS is a great resource if you need to analyze complex survey data. One can easily write code for this by inserting (survey) in front of the procedure with the weight, cluster, and strata variables. (ex: surveyfreq)
Modeling/ Graphing- SAS creates clean and easy to understand graphs and models which take visual data to the next level.
Support- There is a large SAS Advanced analytics online support in place. It is easy to find help on many procedures that you will use in this software.
We've experienced some problems with hanging queries on Redshift Spectrum/external tables. We've had to roll back to and old version of Redshift while we wait for AWS to provide a patch.
Redshift's dialect is most similar to that of PostgreSQL 8. It lacks many modern features and data types.
Constraints are not enforced. We must rely on other means to verify the integrity of transformed tables.
SAS Analytics does not have very good graphic capabilities. Their advanced graphics packages are expensive, and still not very appealing or intuitive to customize.
SAS Analytics is not as up-to-date when it comes to advanced analytical techniques as R or other open-source analytics packages.
Not only does SAS become easier to use as the user gets more familiar with its capabilities, but the customer service is excellent. Any issues with SAS and their technical team is either contacting the user via email, chat, text, WebEx, or phone. They have power users that have years of experience with SAS there to help with any issue.
Just very happy with the product, it fits our needs perfectly. Amazon pioneered the cloud and we have had a positive experience using RedShift. Really cool to be able to see your data housed and to be able to query and perform administrative tasks with ease.
If SAS Enterprise Guide is utilized any beginning user will be able to shorten the learning curve. This is allow the user a plethora of basic capabilities until they can utilize coding to expand their needs in manipulating and presenting data. SAS is also dedicated to expanding this environment so it is ever growing.
SAS probably has the most market saturation out of all of the analytics software worldwide. They are in every industry and they are knowledgable about every industry. They are always available to take questions, solve issues, and discuss a company's needs. A company that buys SAS software has a dedicated representative that is there for all of their needs.
Although nothing is perfect, SAS is almost there. The software can handle billions of rows of data without a glitch and runs at a quick pace regardless of what the user wants to perform. SAS products are made to handle data so performance is of their utmost important. The software is created to run things as efficiently as SAS software can to maximize performance.
The support was great and helped us in a timely fashion. We did use a lot of online forums as well, but the official documentation was an ongoing one, and it did take more time for us to look through it. We would have probably chosen a competitor product had it not been for the great support
SAS is generally known for good support that's one of the main reasons to justify the cost of having SAS licenses within our organization is knowing that customer support is just a quick phone call away. I've usually had good experiences with the SAS customer support team it's one of the ways in which the company stands out in my view.
SAS has regional and national conferences that are dedicated to expanding users' knowledge of the software and showing them what changes and additions they are making to the software. There are user groups in most of the major cities that also provide multi-day seminars that focus on specific topics for education. If online training isn't the best way for the user, there is ample in-person training available.
There are online videos, live classes, and resource material which makes training very easy to access. However, nothing is circumstantial so applying your training can get tricky if the user is performing complex tasks. When purchasing software, SAS will also allocate education credits so the user(s) can access classes and material online to help expand their knowledge.
Ask as many questions you can before the install to understand the process. Since a third party does the installation your company is sort of a passanger and it is easy to get lost in the process. It also helps to have all users and IT support involved in the install to help increase the knowledge as to how SAS runs and what it needs to perform correctly.
Than Vertica: Redshift is cheaper and AWS integrated (which was a plus because the whole company was on AWS). Than BigQuery: Redshift has a standard SQL interface, though recently I heard good things about BigQuery and would try it out again. Than Hive: Hive is great if you are in the PB+ range, but latencies tend to be much slower than Redshift and it is not suited for ad-hoc applications.
We had major use of SAS in forecasting where it doesn't require high level of coding knowledge and which has highly efficient models built in which can give good results on forecasts without lot of manual intervention. This tool was designed specifically for forecasting and hence was always a better choice compared to other tools.
Redshift is relatively cheaper tool but since the pricing is dynamic, there is always a risk of exceeding the cost. Since most of our team is using it as self serve and there is no continuous tracking by a dedicated team, it really needs time & effort on analyst's side to know how much it is going to cost.
It all depends on the type of SAS product the user has. Scaleability differs from product to product, and if the user has SAS Office Analytics the scaleability is quite robust. This software will satisfy the majority of the company's analytic needs for years to come. In addition, if SAS is not meeting the users needs the company can easily find SAS solutions that will.
Our company is moving to the AWS infrastructure, and in this context moving the warehouse environments to Redshift sounds logical regardless of the cost.
Development organizations have to operate in the Dev/Ops mode where they build and support their apps at the same time.
Hard to estimate the overall ROI of moving to Redshift from my position. However, running Redshift seems to be inexpensive compared to all the licensing and hardware costs we had on our RDBMS platform before Redshift.
SAS Advanced Analytics is not the cheapest software on the market. The overall cost was weighed against free, open-source software tools. The overall return, I think, was quite positive because SAS Advanced Analytics saves enormous amounts of time compared to the open-source software tools.
At first, adopting SAS Advanced Analytics was a negative return because it took time for individuals to change their analytics habits and adjust to superior tools available at their discretion.
SAS Advanced Analytics has replaced the need to hire less expensive R or Python programmers. So, although the software requires an initial expensive upfront investment, the ease of use makes it so that other areas of expenditure save money.
