Tue.May 05, 2020

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All you Should Know About Datetime Variables in Python and Pandas

Analytics Vidhya

The Complex yet Powerful World of DateTime in Data Science I still remember coming across my first DateTime variable when I was learning Python. The post All you Should Know About Datetime Variables in Python and Pandas appeared first on Analytics Vidhya.

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COVID-19: Risk Analytics for Building an Early Warning System

Teradata

Advanced analytics & AI techniques can help in curtailing the COVID-19 pandemic. This post describes an analytics prototype to build an early warning system for COVID-19.

Risk 118
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Data Management 20/20: Data Governance Challenges in a Digital Society

TDAN

The reversal from information scarcity to information abundance and the shift from the primacy of entities to the primacy of interactions has resulted in an increased burden for the data involved in those interactions to be trustworthy. If service and results are substandard or wrong, the reputation of the company can more quickly than ever […].

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3 Jenis Laporan Yang Perlu Dipelajari Seorang Business Analyst

FineReport

Dalam kerjaan sehari-hari, ketika dihadapkan kepada pembuatan tabel atau grafik ataupun analisis data, Anda kemungkinan akan memilih Excel. Tapi saya juga melihat banyak orang yang kebingungan dalam rumitnya deep learning Excel dan ketidakefisiennya dalam memproses big data. Faktanya, seorang business analyst profesional harusnya mahir dalam menggunakan berbagai software pembuat laporan (Excel/ QlikView/ Tableau/ FineReport) dan juga mahir dalam membuat berbagai laporan yang berbeda.

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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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Azure Data Sources for Data Science and Machine Learning

Jen Stirrup

Recently, I gave a Make Your Data Work Monday webinar on the complexities of the data sources for data science in Azure, and I thought it important enough to turn into an actual post. If you prefer video, you can catch the video here. How can you differentiate the different opportunities to store your data in Azure? Now, it may not sound that interesting, but it’s crucial; if you don’t have your data, then you don’t have your business.

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Measuring Bias in Machine Learning: The Statistical Bias Test

DataCamp

This tutorial will define statistical bias in a machine learning model and demonstrate how to perform the test on synthetic data.

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Building A World Class Genetics Center Based On Data Scalability

Bruno Aziza

How Regeneron is using Databricks to Build a Genetics Center at Scale.

Big Data 119
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CFO’s Guide to Financially Intelligent Cash Flow Management

Jet Global

Since the onset of the coronavirus crisis, businesses around the world are facing an unprecedented level of uncertainty. In a recent panel discussion of CFOs hosted by insightsoftware , liquidity emerged as the number one priority for C-suite finance leaders. As economic activity has slowed dramatically, many businesses report that sales have plummeted, collections have slowed, and cash flow has become increasingly difficult to predict.

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Finding a Balance With Semi-Supervised Learning

Dataiku

In this blog post, discover how unlabeled data — specifically in the scope of semi-supervised learning — can be used as a “hidden gem” in a variety of machine learning projects.

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Becoming a Data-Driven Company

TDAN

Data-driven companies are more profitable than their competitors and outperform them with regards to the acquiring and retaining of customers [Morris18]. This is a one sentence advertising slogan that explains why so many companies transform their organization and invest into building and expanding their data management and analytics capabilities. Understanding Data Driven “Data-driven company” is […].

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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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Introducing the COVID-19 Data Catalog

Alation

The post Introducing the COVID-19 Data Catalog appeared first on Alation.

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Tales & Tips from the Trenches: Identifying the Right Graph Database – Pt 4

TDAN

As a Data Management professional, it is important to understand the top three challenges of working with graph databases. Modelling Highly Interconnected Data One of the uniqueness of graph databases is its high level of intense expressiveness. This in turn makes it difficult to model a domain on a graph. It is similar to modeling […].

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Empower Your Remote Finance Team with Excel Based Reporting

Jet Global

Finance teams are needing to provide answers to challenging questions which often require new reports and the ability to analyze data in new ways. Working remotely has added a layer of complexity as many finance users rely on IT to build new reports and drill to the information they need. Now, more than ever, you need the right tools to be successful.

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Benefits of Ethical Hacking

TDAN

Cybersecurity is far from being just one thing. To do security well, you need an ecosystem of integrated technologies, procedures, and practices. As technologies like 5G and the Internet of Things (IoT) become more prominent, cybersecurity will also become more complex. The biggest problems facing those who hold data today aren’t necessarily the issues they […].

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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Building Quick, Robust, and Flexible APIs with Data Virtualization

Data Virtualization

Bring any data to any data consumer, simply and easily: that’s the goal of data virtualization. Yet contrary to what may first come to mind, data consumers are more than simply BI, analytics, or data science applications. Just about every.

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Highlights from the 2020 Business Glossary Automation Survey

Octopai

Octopai and Dataversity collaborated to conduct The 2020 Business Glossary Automation Survey. They collected insights from 293 business and IT professionals across a wide range of industries, shining light on why automation metadata operations and the business glossary are priorities for organizations today. They found that manual data management is a process that can bleed hours from a BI team, and the time often turns into days, weeks and even months.

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Corinium Meets: Citi Chief Data Scientist Dan Costanza

Corinium

Dan Costanza, Chief Data Scientist: Banking, Capital Markets and Advisory at Citi, outlines how he’s working to democratize the bank’s data, what’s next for his data strategy and what makes his job is different from other C-Level data roles. What were your greatest professional achievements in 2019? In 2019, our real focus was on increasing engagement with non-data-driven parts of the organization to try to get them to think in a more data-driven fashion.