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Why use Dataknobs Philosophy

Create levers to control and build data products for multiple use cases

CIO

Define how data is being applied

CDO

Improve performance of data org

CPO

Build data products for multiple use cases

Data Officer(s) need to confront complexity of modern enterprise thru multiple data models. Knobs enable interpretation of data & build logical understanding. Most importantly knobs act as levers using which data leaders can control how information is applied in various experiment and AI processes.

Create Datasets

Machine Learning & Reinforcement Learning

Use knobs to define dataset. Efficiently construct dataset that represent real word. Learn optimal policy and generaization with compressed dataset.

Augment datasets

Build robust and complete model

Add more data points, diversity, variability to build dataset that represent world. Generate new dataset to handle cold start problem or test model

Knobs for data privacy

Create levers to make data usable and secure by anonymizing

Remove PII

Text, Images, Speech, structred data

Identify, mask or remove personally identifiable information from datasets. By obscuring PII information, use data for experiments and comply with regulations.

Advance anonymization

Privacy preserving anonymization

Anonymize data to protect against identify,membership and attribute disclosure. Protect the privacy as well as make data useful for getting insight.

Knobs for Generative AI

Create levers to genrate data, generate websites & build data products

Generate websites

Publish content as websites

Focus on producing content and data. Generate web experience , mobile epxerience. Using knobs optimize for presentation layer, speed, distribution, SEO

Kreate Chatbot

Integrated chatbot and knowledgebase

Fine tune LLM for specific task and build custom chatbot. Build intranet, knowledgebase and chatbot. Automatically retrain chatbot, digital assistant as new help article arrives.

From the blog

Build Dataproducts

How Dataknobs help in building data products

Enterprises are most successful when they treat data like a product. It enable to use data in multiple use cases. However data product should be designed differently compared to software product.

Well governed data

Data Lineage and Extensibility

To build a commercial data product, create a base data product. Then add extension to these data product by adding various types of transformation. However it lead to complexity as you have to manage Data Lineage. Use knobs for lineage and extensibility

Innovate with experiments

Experiment faster and cheaper with knobs

In complex problems you have to run hundreds of experiments. Plurality of method require in machine learning is extremely high. With Dataknobs approach, you can experiment thru knobs.

Spotlight

Why knobs matter

They hold things together

Data is new Intellectual property (IP). Data generated thru business process is important, Augmented data for Macine Learning, Data created , transformed to fuel new use cases in AI is also an IP.

Generality of AI product depends on variety of data you you. To build universal dataset for AI product you need many approaches to build gold dataset. Data knobs enable you manage and generate datasets.