Ignithos Customer Data Platform Accelerator
Pandas
NumPy
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
Ignitho’s CDP accelerator allows implementations in as little as 2 weeks. By keeping the AI use cases front and center, the CDP accelerator provides an integrated solution framework. The CDP accelerator is industry specific and comes bundled with predefined AI models to cater to the most important use cases. This ensures that your implementations are rapid and meet a very tangible business need.
If additional AI models are needed, they can be added quickly making the accelerator very scalable.
Your CDP implementation is not just an aggregated repository of customer data with visualizations and basic segmentations.
View a demo of our CDP Accelerator that provides an integrated solution framework. https://dashboard.mailerlite.com/forms/425317/88596354137327168/share
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Ignithos Customer Data Platform Accelerator's answer
Microsoft, DOMO, AWS, Snowflake, Databricks
Ignithos Customer Data Platform Accelerator's answer
Our Primary audience are the enterprises who need customer data analytics in Retail, Media, healthcare, fintech industry.
Ignithos Customer Data Platform Accelerator's answer
Ignitho’s CDP accelerator allows implementations in as little as 2 Weeks.
Ignithos Customer Data Platform Accelerator's answer
By keeping the AI use cases front and center, the Ignitho's CDP accelerator provides an integrated solution framework. As the power of AI becomes more accessible, digital first organizations must embrace the concept of the CDP to enhance the effectiveness of customer analytics. The following are some key takeaways: 1. Integration of AI insights into business applications using APIs must remain top of mind to maximize the business impact 2. A balanced coupling between the enterprise data lake and a CDP must be created. Data does not always have to be duplicated, and even if duplicated there are ways to provide the updates back to the source systems. 3. Choice of platform ranges from custom to a licensed product. A CDP accelerator can offer a good balance. Make a choice after considering your requirements and tech landscape.
Based on our record, Pandas seems to be more popular. It has been mentiond 200 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Pandas - A powerful data analysis and manipulation library for Python. Pandas Documentation - Official documentation. - Source: dev.to / 6 days ago
It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / about 1 month ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / about 2 months ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / about 2 months ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 4 months ago