My main use case for AlphaSense is competitor analysis. For competitor analysis, I look for competitor interviews where they could have said something that could reveal important information.
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My main use case for AlphaSense is competitor analysis. For competitor analysis, I look for competitor interviews where they could have said something that could reveal important information.
The best features AlphaSense offers are how effective it is at finding information. AlphaSense presents interviews and gives me the entire transcripts of certain interviews with a competitor and their potential or existing customers, which makes it very helpful for me to understand what their positives and negatives are.
AlphaSense has positively impacted my organization by helping bring in more leads and tailoring our emails better. I have seen a definite 15% increase in the number of leads that are being converted.
I have been using AlphaSense for a few months now, so it is hard to tell or criticize. So far, I cannot find any issues.
I have been using AlphaSense for two months.
I would advise others looking into using AlphaSense that it is definitely a tool to look into. I would rate this product a 10 out of 10.
In general, I have had a good experience with Oracle Cloud Infrastructure (OCI), even though my current company uses other cloud providers such as AWS and Azure. With GoldenGate on Oracle Cloud Infrastructure (OCI), we find it works well, and because we use many Oracle technologies on-premise, it is simpler to access and use Oracle Exadata and other tools with Oracle Cloud Infrastructure (OCI). I think Oracle Cloud Infrastructure (OCI) is a very good choice today to use and to recommend to other customers.
I have not used Oracle Cloud Infrastructure (OCI)'s AI and machine learning features in active projects, though I obtained certification in AI Vector and have attempted to use these technologies. There are other software teams that may be trying to use it, but as a database administrator, my responsibility does not currently involve active AI implementation. I have only laboratory experience with these features.
I would describe the advantages of Oracle Cloud Infrastructure (OCI) in facilitating large-scale migrations as something we usually do not use, even though I obtained a certification and understand how the tool works. What typically happens is that we perform an initial stream of the structure between source and target. Then with Oracle Data Pump, we may perform the streaming of the data. If we can use tools such as GoldenGate, we can perform a separate installation and keep the two databases synchronized between source and target. In another use case, if data changes are not frequent, we use other strategies, such as materialized view logs. We can perform an initial loading of the data and then align only the tables whose data is changing through the use of materialized view logs. We use different strategies for different use cases, but we do not use Oracle Cloud Infrastructure (OCI) tools to perform this today.
I think that next year, we can start to use Oracle Cloud Infrastructure (OCI)'s technologies for data analytics capabilities because we now work in the health sector. AI Vector can help us for our use cases to search and find information in tables. I believe we will use it as soon as possible.
In my previous company, Oracle Cloud Infrastructure (OCI)'s cost management tools helped us create a map of the cost of the various objects and services. I think that is very useful.
I have not used Oracle Cloud Infrastructure (OCI)'s networking solutions today. I studied it somewhat, but it is not my main area currently.
We had some problems sometimes with Autonomous Database in Oracle Cloud Infrastructure (OCI), for example, in the past months related to the asset of the metrics. We found problems related to what we wanted to show to the customer about the database because many metrics were missing. We usually worked together with members of Oracle Italia to ask them to introduce some metrics, for example, those that do not work correctly about CPU usage, memory usage, or network usage. There were some metrics in Oracle Autonomous Database in dedicated infrastructure that did not allow us to show correct information to the customer. We usually needed to ask Oracle Italia to introduce some metrics or clarify metric usage. In some cases, they showed incorrect data in the output, so we had to work with them to solve this problem. I am speaking about problems from approximately one year ago, so I do not know if they have fixed all of it now.
One problem I faced in the past with Oracle Cloud Infrastructure (OCI) was also related to documentation. Sometimes there are differences between Oracle Autonomous Database usage on shared infrastructures compared to dedicated infrastructures. When searching for documentation, it is not clear if one aspect or solution is usable in both technologies or on both shared and dedicated infrastructures. I found some documents proposed for Autonomous Database and then discovered that the case was applicable only for shared infrastructure, not dedicated. Oracle Italia explained to me that Oracle Autonomous Database on shared and dedicated are different products. However, I do not understand why if I have the same version of Oracle in both architectures, I cannot have access to some tools or internal packages in both technologies. We usually had to ask them to introduce also in dedicated infrastructures the use of some Oracle PL/SQL packages, some internal packages, for example, for the management of queues.
Another aspect is that the storage of Oracle is not very user-friendly. In Autonomous, for example, where I think an autonomous database should manage storage correctly on its own, my experience is that often we have many allocated storage spaces that are free, but it is impossible to reclaim. We need to expand storage and pay for it, even though it is free. I think that regarding the internal management of storage, Oracle can improve.