Ignithos Customer Data Platform Accelerator
Jupyter
Looker
Databricks
Google BigQuery
Presto DB
Rakam
Informatica
Concurrent
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.
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JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / 20 days ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / about 1 month ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / 26 days ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 2 months ago
Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / 2 months ago
