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Mailchimp’s ex-Head of Data Platform: “Data Doesn’t Have to be Hard — Three Data Myths and How to Bust Them”

SaaStr

Data Doesn’t Have to be Hard: Three Data Myths and How to Bust Them with Mailchimp with John Humphrey, former Head of Data Platform Product at Mailchimp John Humphrey, former head of data platform product at MailChimp and current principal at mfact, joined SaaStr live at Workshop Wednesday to discuss three data myths and how to debunk them.

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Managing Data as Product : Office Hours with Philip Zelitchenko

Tom Tunguz

am Pacific, Office Hours will host Philip Zelitchenko , VP of Data at ZoomInfo to discuss Managing Data as Product. Recently, Philip shared his management techniques to run a data team like a standard product software development function with some key nuances. On December 14th at 9.30

Data 149
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Klaviyo: Benchmarking the S-1 Data

Clouded Judgement

Klaviyo Overview From the S1 - “Klaviyo enables businesses to drive revenue growth by making it easy to bring their first-party data together and use it to create and deliver highly personalized consumer experiences across digital channels. ” “Data Layer. ” “Data Layer.

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The Rise of Data Lakes in Software Architecture

Tom Tunguz

Historically, software-as-a-service (SaaS) has been built on databases with structured data, as you might find in an Excel spreadsheet. But the ability of large language models to extract insights from unstructured information changes this architecture : data repositories like data lakes are becoming essential parts of modern SaaS stacks.

Software 257
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Modern Data Architecture for Embedded Analytics

Every data-driven project calls for a review of your data architecture—and that includes embedded analytics. Before you add new dashboards and reports to your application, you need to evaluate your data architecture with analytics in mind. Expert guidelines for a high-performance, analytics-ready modern data architecture.

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Top 10 Trends for Data in 2024

Tom Tunguz

At the IMPACT Summit yesterday, I shared our Top 10 Trends for Data in 2024. LLMs Transform the Stack : Large language models transform data in many ways. First, they have driven an increased demand for data and are causing a complete architecture inside companies. Second, they change the way that we manipulate data.

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Top 10 Trends in Data & AI at the Impact Summit

Tom Tunguz

On November 8th, I’ll share my 10 Top Trends in Data & AI at the IMPACT Summit. Last year, I covered 9 topics: Cloud data warehouses will process 75% of workloads by 2024. Data workloads segment into in-memory, cloud data warehouse, & cloud data lakes. Metrics layers unify the data stack.

Trends 203
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5 Things a Data Scientist Can Do to Stay Current

Demand for data scientists is surging. With the number of available data science roles increasing by a staggering 650% since 2012, organizations are clearly looking for professionals who have the right combination of computer science, modeling, mathematics, and business skills. Collecting and accessing data from outside sources.

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4 Approaches to Data Analytics

The world of data analytics is changing fast as organizations look to gain competitive advantages through the application of timely data.

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Data Science Fails: Building AI You Can Trust

The new DataRobot whitepaper, Data Science Fails: Building AI You Can Trust, outlines eight important lessons that organizations must understand to follow best data science practices and ensure that AI is being implemented successfully. Download the report to gain insights including: How to watch for bias in AI.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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Monetizing Analytics Features: Why Data Visualization Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Download the whitepaper to learn about Monetizing Analytics Features, and Why Data Visualizations Will Never Be Enough. Five years ago they may have. But today, dashboards and visualizations have become commonplace.

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How Banks Are Winning with AI and Automated Machine Learning

Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Brought to you by Data Robot.

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How Banks Are Winning with AI and Automated Machine Learning

Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Brought to you by Data Robot.

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Contact vs. Company Intent Signal Data

Contact and company intent data both have their advantages. This infographic unpacks the advantages of both contact and company data and gives details about how B2B marketers can benefit from both. This infographic unpacks the advantages of both contact and company data and gives details about how B2B marketers can benefit from both.