Mon.Sep 14, 2020

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All Aboard the Pandas Express – How to Speed up Data Preprocessing using Pandas in Python

Analytics Vidhya

Overview Pandas is the Swiss Army Knife of data preprocessing tasks in Python but can be cumbersome when dealing with large amounts of data. The post All Aboard the Pandas Express – How to Speed up Data Preprocessing using Pandas in Python appeared first on Analytics Vidhya.

Analytics 398
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7 Ways To Prevent Data Breaches With Technology And Training

Smart Data Collective

There is a common misconception prevalent amongst businesses that cyberattacks , and data breaches only target large scale enterprises. This is not true as almost half of the cyberattacks target small to midsize businesses. This misconception prevents businesses from taking data breaches and cybersecurity attacks seriously. They not only ignore it but also do nothing to protect themselves from it.

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How to perform Blur Detection using OpenCV in Python

Analytics Vidhya

Introduction In the corona days (still not over) I would walk near my house for an hour a day and come back home. One. The post How to perform Blur Detection using OpenCV in Python appeared first on Analytics Vidhya.

Analytics 306
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Utilizing Data Analytics To Create Seamless Web Dashboards

Smart Data Collective

Big data is radically changing the future of online business. The benefits that it offers are abundantly clear. This Medium post highlights some of the reasons that big data is transforming the nature of e-commerce and other fields of online business. One of the biggest benefits is through personalized recommendations. Amazon receives around 35% of its business through recommendations it provides to customers.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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The Game Has Changed for Retail – or Has it?

Teradata

The game had changed for the retail sector long ago – but it has taken the COVID-19 crisis for people to notice. A new appreciation for the role of data in retail has emerged.

IT 93
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Employee Spotlight: Building and Iterating on DataCamp’s Products

DataCamp

Q&A with Sue Lai, VP of Product at DataCamp

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Applying Zero-based Budgeting to Get Zero-Based Analytics

Andrew White

How many times are you asked to justly the Analytics and BI team or the work they regularly undertake in behalf of the business? If you are responsible for supporting or producing insight as a service to your business counterparts, which is a common capability in many IT organizations, then you will be familiar with the question posed. As the COVID-19 crisis wound on, you most likely heard the question several times, and you didn’t have to wait for the annual budget cycle.

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What is Metadata Management?

Octopai

Modern data processing depends on metadata management to power enhanced business intelligence. Metadata is of course the information about the data, and the process of managing it is mysterious to those not trained in advanced BI. In this article, you will learn: What does metadata management do? What is metadata management? How do metadata management tools work?

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Diversity and Inclusion at Nutanix: Where we’ve been, where we’re headed

Nutanix

While we move ahead in making Nutanix a fantastic place to work for all of our employees, I know simultaneously that we still have a long way to go on our journey.

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Fundamentals for Success in Cloud Data Management

Cloudera

Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users. Data architects deal with constantly evolving workloads and business analysts must balance the urgency and importance of a concurrent user population that continues to grow.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Diversity and Inclusion at Nutanix: Where we’ve been, where we’re headed

Nutanix

While we move ahead in making Nutanix a fantastic place to work for all of our employees, I know simultaneously that we still have a long way to go on our journey.

20
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Databases and Machine Learning Coalesce

Sanjeev Mohan

The boundaries between data management and advanced analytics are blurring fast. Databases are enhancing capabilities to build, train and validate machine learning models right where the data sits – inside the databases and data warehouses. When the ML operations and the data-preparation are in separate artifacts, the round-trip for investigative analytics is long and ponderous.

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The Challenges of Model Maintenance in 2020 [Infographic]

Dataiku

Building an Enterprise AI strategy that is fit to carry the business through economic highs and lows isn’t just about implementing a list of use cases and leveraging reuse to expand on those use cases. It’s also pivotal to have systems for monitoring models in production and to be able to quickly introduce, test, train, and implement new models in order to shift strategies or adapt to changing environments on a dime.