Mon.Dec 05, 2022

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Why Data Migrations Suck.

Confessions of a Data Guy

I’ve often wondered what purgatory would be like, doing penance for millennia into eternity. It would probably be doing data migrations. I suppose they are not all that dissimilar from normal software migrations, but there are a few things that make data migrations a little more horrible and soul-sucking. Data migrations are able to slow […] The post Why Data Migrations Suck. appeared first on Confessions of a Data Guy.

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How Artificial Intelligence Will Change Mobile Apps

KDnuggets

There are numerous ways in which Artificial Intelligence (AI) will change the way we use mobile apps. As more and more users shift towards tablet computers and various mobile platforms, developers are coming up with new ideas for improving user experience. AI holds many key factors for the future of mobile app development and could indeed prove to be a game changer on almost all fronts.

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Teradata VantageCloud Lake + Vcinity Technology: Taking the Management Costs out of Network Latency

Teradata

Teradata VantageCloud Lake + Vcinity is perfect for on-premises, hybrid, & multi-cloud solutions where long network latency might keep an enterprise from leveraging access to their sensitive data.

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Top Posts November 28 – December 4: The Complete Data Engineering Study Roadmap

KDnuggets

The Complete Data Engineering Study Roadmap • How to Select Rows and Columns in Pandas Using [ ],loc, iloc,at and.iat • Top 10 Data Science Myths Busted • What is Chebychev’s Theorem and How Does it Apply to Data Science? • Scikit-learn for Machine Learning Cheatsheet.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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From Hunger to Hedgehogs: Clouderans Drive Impact in 2022 Through Global Volunteering Efforts

Cloudera

Clouderans in 2022 have collectively donated hundreds of hours to causes they care about around the globe. This kind of support for nonprofits is essential to their running, and to driving impact in local communities. For International Volunteer Day 2022, we are excited to celebrate Cloudera’s volunteer spotlights from 2022! . “ I believe it is important to work with people and organizations that share common values to achieve their goals.”.

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Introduction to Data Visualization Using Matplotlib

KDnuggets

Data Visualization is an important aspect of Data Science that enables the data to speak for itself by uncovering the hidden details. Follow this guide to get started with Matplotlib which is one of the most widely used plotting libraries in Python.

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A Brief Introduction to Kalman Filters

KDnuggets

What you can’t observe, you ought to estimate. Human evolution is based on this keen interest in measurement. But what are the quantities or phenomena which you can’t observe or measure with certainty? Learn this and more about Kalman Filter which is the most widely used algorithm to estimate a true quantity.

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How Acceldata Revamped Data Observability at PhonePe at the Infrastructure Layer

Acceldata

Learn how Walmart subsidiary PhonePe adopted Acceldata’s Data Observability solution which helped them improve productivity by minimizing everyday data emergencies and data downtime.

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User Notification: SYSTEM$SEND_EMAIL()

Cloudyard

Read Time: 2 Minute, 14 Second During this post we will discuss latest feature in snowflake i.e. User Notification: SYSTEM$SEND_EMAIL() Stored Procedure. Snowflake has introduced a new mechanism to notifying users based on monitoring and administrative email notification with in the same account. SYSTEM$SEND_EMAIL() uses the notification integration object, which is a Snowflake object that provides an interface between Snowflake and third-party services (e.g. cloud message queues, email, etc.

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Optimize Hadoop Operational Efficiency By 30%

Acceldata

Acceldata’s data observability Pulse product is specifically designed to improve reliability, scale, and cost for HDP/CDH. It's a highly optimized solution that gives you options to keep your HDP/CDP on-premises or migrate to the cloud data warehouses of your choice on your own timeframe.

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Understanding User Needs and Satisfying Them

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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How PayJoy Drives Data Trust with Monte Carlo

Monte Carlo

PayJoy is on a mission to bring credit to the next billion people in emerging markets around the world. Using their own proprietary mobile security technology, PayJoy gives customers the ability to afford their first smartphone on credit. With millions of customers across a dozen countries and support from major industry partners, data reliability plays a key role in PayJoy’s ability to not only deliver on their brand’s promise but also understand their performance and make mission-critical deci

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Optimizing the Modern Data Stack with Enterprise Data Observability

Acceldata

Simply “monitoring” certain pieces of the data stack doesn’t go far enough. That’s why taking a multidimensional approach to enterprise data observability is key for gaining a comprehensive understanding of the organization’s data, processing, and pipelines.

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How Data Observability Goes Far Beyond Data Quality Monitoring and Alerts

Acceldata

The cost of poor quality and unreliable data is set to skyrocket as companies transform into data-driven digital enterprises. Access to data, therefore, is critical, but ensuring that that data is reliable becomes absolutely mission-critical.

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How Data Observability Promotes Data Product Development

Acceldata

Data products use continuously available data from an organization's data stack. Data observability helps ensure data quality and reliability so enterprise can deliver quality data products.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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Building Better Data Products with Data Observability

Acceldata

Data products—such as data-driven dashboards, visualizations, reports, models, and other processes that make it easier to leverage data—have become vital tools for companies of all sizes across virtually every industry.

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Employee Spotlight: Raghu Mitra, Co-founder & Director of Engineering, Acceldata

Acceldata

Acceldata’s co-founder and Director of Engineering, Raghu Mitra, started his career as a software engineer in 2005. He quickly realized he enjoyed problem-solving, and the world of data had a huge problem: projects were almost impossible to complete, and that struck a chord with him. Raghu provides insight into this revelation, his part in Acceldata’s founding, and what his typical day looks like as a co-founder at the enterprise data observability leader.

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Data Observability Provides the Foundation for Data Quality at Scale

Acceldata

Enterprise data teams can’t rely on manual interventions to improve data quality at scale. They need a data observability solution with advanced AI/ML capabilities to automatically detect data and schema drift, anomalies, as well as lineage.

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4 Foundational Principles for Building a Data-Driven Culture

Acceldata

Digital transformation is clearly important, but it’s not the only factor to consider. Becoming data-driven is another key part of the journey, but getting there isn’t easy.

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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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5 Ways Data Observability Can Reduce Your Confluent Cloud Kafka Cost

Acceldata

Streaming data has become a requirement for enterprises to build and operate great data products, and Apache Kafka is far and away the standard for real-time streaming.

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How Data Observability Can Deliver 80X ROI

Acceldata

Optimizing enterprise-scale data infrastructure and operation costs is a big challenge, and data observability can be a driver of both cost savings and high ROI.

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4 Ways Data Observability Improves the Cloud Migration Process

Acceldata

Your cloud migration process must include a multidimensional observability solution that provides a granular view of your data and infrastructure layers.

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6 Ways To Get Real-Time Intelligence Of Your Hadoop Ecosystem

Acceldata

For real-time insights into your Hadoop environment, you need a solution like Acceldata. Real-time intelligence and auto-generated recommendations.

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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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Value Engineering and Data Cost Optimization Through Data Observability

Acceldata

This blog defines data cost optimization and explores why multi-dimensional data observability is an enabler for value engineering best practices.

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How Data Observability Can Turn You Into a Cloud Data FinOps Expert

Acceldata

What can cloud FinOps professionals do to get a handle on the ROI of their data operations and pipelines? Here’s how data observability can help.

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Data Engineering: How Spotify Upgraded its Data Orchestration Platform

Acceldata

PlatformsLearn how Spotify leverages data orchestration to run 20,000 batch data pipelines defined in more than 1,000 repositories every day.

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PubMatic Leverages Acceldata’s Data Observability Platform to Optimize Performance and Cost at Massive Scale

Acceldata

Case study of how PubMatic leverages Acceldata’s Data Observability platform to optimize performance and cost at massive scale.

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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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Why Automating ETL Validation Scripts Will Improve Data Validation

Acceldata

ValidationLearn how a data observability solution can automatically clean and validate incoming data pipelines in real-time.

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5 Steps to Operationalize Data Product Development

Acceldata

Developing data products involves many moving parts. Here's a framework for operationalizing data product development.

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Do You Know When Good Data Goes Bad?

Acceldata

Data quality is achieved through data observability and allows you to assess how reliable your enterprise data is.

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Data Observability Checklist: How to Choose the Right Solution

Acceldata

Free checklist that provides an at-a-glance introduction to nineteen important data observability features.

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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