data science - Rittman Mead

Oracle Powered RAG - Revisiting our Chatbot

Back in March, we demonstrated a chatbot that uses RAG to allow users to query the content of our blog using natural language. It made use of OpenAI’s API to access their embedding models and the GPT 3.5 turbo Large Language Model (LLM), and used Weaviate as the

data science

Deploy RStudio in an OCI Container

RStudio is a free interactive development environment or (IDE) designed specifically for the R language. It supports direct code execution, and tools for plotting, history, and debugging. It’s safe to say that almost no-one uses R without R Studio. RStudio Server is an application that provides a web based

data science

4 Behaviours Separating Good Data Science From Great Data Science

For the interest of data scientists and data owners looking to improve their approach to data science projects, this post looks at a few ways we can take good data science practices and elevate them to great ones. Data science, at its heart, is a methodology for extracting insights and

data science

Introduction to Oracle Data Science Service Part 4

This post is the fourth part of my blog series on the Oracle Data Science Service. In the previous post here we looked at some of the capabilities of the Oracle ADS SK, as well as creating, saving, and deploying models to OCI. In this blog we will look at

data science

Introduction to Oracle Data Science Service Part 2

Using oracle-ads Python library to create a secret within an OCI vault. Use this secret to connect to an ADW and read and write data to the AWD.

data science

Introduction to Oracle Data Science Service Part 1

Creating Data Science Projects and Notebook Sessions, installing and creating kernel environments, and sharing these environments via the OCI Storage Bucket.

OAC

Democratize Data Science with Oracle Analytics Cloud - Predictions and Final Considerations

Oracle Analytics Cloud as an enabler for Data Science: this is the third post of a series which started with Episode I [http://ritt.md/OAC-datascience] where we discussed the path from a Data Analyst to a Data Scientist and how to start a Data Science journey with OAC. Episode

OAC

Democratize Data Science with Oracle Analytics Cloud - Data Analysis and Machine Learning

Welcome back! In my previous Post [http://ritt.md/OAC-datascience], I described how the democratization of Data Science is a hot topic in the analytical industry. We then explored how Oracle Analytics Cloud can act as an enabler for the transformation from Business Analyst to Data Scientist and covered the

OAC

Democratize Data Science with Oracle Analytics Cloud

Oracle Analytics Cloud bridges the gap between Business Analysts and Data Scientist by providing Augmented Analytics and a easy path to Machine Learning.

cloud

Oracle OpenWorld Europe : London 2019

Some eleven thousand people descended on Oracle OpenWorld Europe in London last week for two days of business and technical sessions delivered by a mixture of members of Oracle’s product team and end users giving real-world case studies of adoption of Oracle’s Cloud offerings and product roadmaps. Something

data science

Common Questions and Misconceptions in The Data Science Field

There are many types of scenarios in which data science could help your business. For example, customer retention, process automation, improving operational efficiency or user experience. It is not however always initially clear which questions to concentrate on, or how to achieve your aims. This post presents information about the

OBIEE12c

A focus on Higher Education, HEDW 2017

First, before I get into a great week of Higher Education Data Warehousing and analytics discussions, I want to thank the HEDW board and their membership. They embraced us with open arms in our first year of conference sponsorship. Our longtime friend and HEDW board member, Phyllis Wykoff, from Miami

training

What's new in Training in 2017?

2016 - Thank you for a great year! Rittman Mead would like to thank everyone that attended or showed an interest in our Training courses in 2016. Since we started back in 2007, Training has been a mainstay of our service offerings. My personal opinion is that Q3 & Q4

Big Data

Using Jupyter Notebooks with Big Data Discovery 1.2

New in Big Data Discovery [https://www.oracle.com/big-data/big-data-discovery/index.html] 1.2 is the addition of BDD Shell, an integration point with Python. This exposes the datasets and BDD functionality in a Python and PySpark environment, opening up huge possibilities for advanced data science work on BDD

Big Data

Running Big Data Discovery Shell and Jupyter Notebook on Big Data Lite VM 4.5

New in Big Data Discovery [https://www.oracle.com/big-data/big-data-discovery/index.html] 1.2 is the addition of BDD Shell, an integration point with Python. This exposes the datasets and BDD functionality in a Python and PySpark environment, opening up huge possibilities for advanced data science work on BDD