Arcadia Data (discontinued) vs. IBM Analytics Engine

It is suitable for companies without a proper data warehouse. He does very well in sales analysis and KPI management. It builds mini data warehouses, is good at data fusion, and interfaces well with other systems. Also, the export function and filter can greatly help you to get only the information you want in the format you want.

Incentivized

• Well suited for my big data related project or a static data set analysis especially for uploading huge dataset to the cluster.
• But had some issues with connecting IoT real-time data and feeding to Power BI. It might be my understanding please take it as a mere comment rather than a suggestion.

Incentivized

• Coding is also simple and can be learned easily.
• It is my favorite because it shows how mathematical models are used in real life.

Incentivized

• Jobs with Spark, Hadoop, or Hive queries are rapidly attained
• Can collect, organize and analyze your data accurately
• You can customize, for example, Spark or Hadoop configuration settings, or Python, R, Scala, or Java libraries.

Incentivized

• You have to make sure that the information thrown makes sense and is well organized.
• There is a risk when saving information in the cloud from computer attacks

Incentivized

• Easier pricing and plug-and-play like you see with AWS and Azure, it would be nice from a budgeting and billing standpoint, as well as better support for the administration.
• Bundling of the Cloud Object Storage should be included with the Analytics Engine.
• The inability to add your own Hadoop stack components has made some transfers a little more complex.

Incentivized

We can easily provide the information that the user wants and customize it according to their needs. Sometimes a certain report can be used as the basis for creating another one that saves you time to deliver critical information in the shortest amount of time with the best results. Builds mini data warehouses, is good at data fusion, and interfaces well with other systems.

Incentivized

I love how easy it is to create prototypes due to its simple simulation and modeling system. Other than that, the codes are usually simple and not very complex and it's built-in debugging adds to that ease. is an excellent tool for analyzing, classifying, and visualizing data. I do this most of the time to help me grab huge collections of data.

Incentivized

You can have a good reading of the data, you undoubtedly have cost savings and eliminate unnecessary and repetitive processes, we have unstructured data that, when structured, are elements of information that have become a competitive advantage for our organization, it is undoubtedly a strategic ally for the organization in the decision-making process

Incentivized

We initially wanted to go with Google BigQuery, mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM. Apache Spark was also in the running, but here IBM's domination in the industry made the choice a no-brainer. As previously stated, the support received was not quite what we expected, but was adequate.

Incentivized

• Download the report data only in Excel. Unable to download report formats such as colors, fonts, etc.
• It does not support the presentation of images of our products as part of the analysis.

Incentivized

• This product has allowed us to gather analytics data across multiple platforms so we can view and analyze the data from different workflows, all in one place.
• IBM Analytics has allowed us to scale on demand which allows us to capture more and more data, thus increasing our ROI.
• The convenience of the ability to access and administer the product via multiple interfaces has allowed our administrators to ensure that the application is making a positive ROI for our business users and partners.

Incentivized