Resources
Blogs, videos, case studies and announcements from our team
Finding Conversion Anomalies at a Large E-Commerce Firm
Learn how a leading multi-billion dollar e-commerce company used Enrich to identify anomalies in their conversion rates and to find out their causal factors.
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Streamlined data insights and agile data preparation for Terrapay
Learn how Terrapay, a leading cross-border payment infrastructure solution provider built the Terrapay Intelligence Platform (TIP) with Enrich to achieve operational efficiency through use cases such as Forecasting, Partner Performance Analytics, Customer Journey Analytics, and more.
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Managing The Organizational Impact of Bad Data
Big data is an indispensable part of our modern existence, powering several real-world applications such as personalized marketing, healthcare diagnostics, fraud prevention and many more that have transformed the way we live, work, and communicate with each other. However, since big data has become such a critical component of organizational decision-making, it is imperative to […]
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The Future of Data Product Development: Exploring Key Trends
The year is 2023, and Sarah, a data analyst at a leading tech firm, no longer spends hours writing complex SQL queries or sifting through vast datasets. Instead, she simply asks her data product, powered by a Large Language Model (LLM), “What were the sales trends last quarter?” and receives a comprehensive, human-like response. This […]
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Mastering Generative AI: A comprehensive guide
The year was 2018. Art enthusiasts, collectors, and critics from around the world gathered at Christie’s, one of the most prestigious auction houses. The spotlight was on a unique portrait titled “Edmond de Belamy.” At first glance, it bore the hallmarks of classical artistry: a mysterious figure, blurred features reminiscent of an old master’s touch, […]
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Navigating the Data Landscape: A Deep Dive into Warehouses, Lakes, Meshes, and Fabrics
It’s your first day at “TechTonic Innovations,” a (fictional) startup that’s been making waves in the tech industry. As you enter their modern office, you’re greeted with smiles, handshakes, and the subtle hum of servers in the background. You’ve been brought in as the new Data Strategist, and you’re eager to dive into the heart […]
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From Data to Decisions: How Generative AI is Transforming Enterprise Analytics
It’s the 24th century aboard the Starship Enterprise. Captain Jean-Luc Picard, in need of a break from the rigors of interstellar diplomacy, steps into the Holodeck. This isn’t just any room; it’s a technological marvel, a space where any scenario can be simulated, any world, any reality can come to life. Picard chooses a 1940s […]
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Deploying Responsible AI: Big Picture Questions and Strategies
At Scribble Data, our goal is to help organizations make better decisions with data. Over the last year, rapid advancements in Generative AI (GenAI), large language models (LLMs) and natural language processing (NLP) have been a shot in the arm for us. These innovations inspired us to launch Hasper, our machine learning and LLM-based data […]
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Data Fabric: Unraveling the Future of Integrated Data Management
Scene 1: Picture waking up to the soft strumming of the acoustic guitar on Bon Iver’s “Holocene”, a song recommendation from Spotify based on your recent obsession with indie folk. Scene 2: As you sip your morning coffee, you scroll through your Amazon app, noticing a recommendation for a book on “Modern Folklore and Music.” […]
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From Raw Data to Revolutionary Insights: A Deep Dive into Data Product Architecture
The Oakland Coliseum was abuzz, the air thick with anticipation. In the dimly lit back office, Billy Beane, the General Manager of the Oakland Athletics, sat hunched over a cluttered desk. Papers were strewn everywhere, but Billy’s focus was on a single sheet filled with numbers, statistics, and player names. The Athletics, with one of […]
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Overfitting and Underfitting in ML: Introduction, Techniques, and Future
In 2016, the tech world was all ears and eyes. Microsoft was gearing up to introduce Tay, an AI chatbot designed to chit-chat and learn from users on Twitter. The hype was real: this was supposed to be a glimpse into the future where AI and humans would be best buddies. But, in a plot […]
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Zero Shot Learning: A complete guide
In the realm of the big screen, there’s a man who needs no introduction. A man of resourcefulness, a man of ingenuity, a man who could turn a paperclip into a key to conquer the most impossible of missions. His name? Ethan Hunt. He is the embodiment of the idea that necessity is the mother […]
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Synthetic Data in Machine Learning: Introduction, Applications, and Future
Picture this: You’re in the world of “Inception,” Christopher Nolan’s cinematic masterpiece. Dream architects are crafting intricate labyrinths within dreams, creating realities so convincing that the dreamer can’t tell they’re asleep. They are bending the fabric of the dream, shaping it to their will, whether it’s a heart-pounding chase through a bustling market or a […]
Read MoreCase Studies
Finding Conversion Anomalies at a Large E-Commerce Firm
Learn how a leading multi-billion dollar e-commerce company used Enrich to identify anomalies in their conversion rates and to find out their causal factors.
Read More
Streamlined data insights and agile data preparation for Terrapay
Learn how Terrapay, a leading cross-border payment infrastructure solution provider built the Terrapay Intelligence Platform (TIP) with Enrich to achieve operational efficiency through use cases such as Forecasting, Partner Performance Analytics, Customer Journey Analytics, and more.
Read More
How Mars Took Steps to Evaluate the Potential Impact of the “Great Resignation”
Learn how Mars, a Fortune 100 CPG company collaborated with Scribble Data to assign a “probability of attrition” through data, and ML modeling.
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Accelerated ML Engineering for a Leading E-Commerce Brand
Learn how a leading e-commerce brand selling children’s apparel built their data intelligence platform on Scribble Data that supported the rapid development and deployment of use cases such as Product Listing Optimization and Re-ordering.
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Understanding Shopping Paths at a National Mall Chain
Learn how a nationwide mall chain used Scribble Data’s Enrich platform to identify patterns of shopper footfalls, determine the timing and location of ads, and achieve a significant M-o-M increase in revenue.
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A National Level Retail Store Chain
A national level retail chain in India leverages Scribble Data Enrich for developing an accurate understanding of their buyer personas, their distribution, demand and context at a fine granularity to address multiple operational use cases.
Read MoreVideos
Lifecycle of a Data Product with Dr. Venkata Pingali
Watch this session where Dr. Venkata Pingali, Founder & CEO of Scribble data shares his perspective on Data Products, the types of Data Products, and the lifecycle of Data Products with the Data Heroes community.
Watch NowCustomer Testimonial: Cloudphysician
Dileep Raman, Cloudphysician’s Co-founder and Chief of Healthcare, talks about how Scribble Data enabled them to rapidly build pipelines to transform their data and get daily updated feature sets as well as trustworthy models – all in less than 4 weeks!
Watch NowCustomer Testimonial: Mars, Inc.
Dr. Vidyotham Reddi of Mars, Incorporated–a leading US-based multinational CPG manufacturer of confectionery, pet food, and other food products and a provider of animal care services, talks about his experience of working with Scribble Data. Learn how his team at Mars was able to assign a “probability of attrition” to employees, calculated based on which […]
Watch NowWhat’s the deal with sentient AI? – Achint Thomas
Sentience in AI has always been the holy grail for computer science. What qualifies as AI sentience, and what is just another case of a model mimicking the data it’s trained on?
Watch NowAnatomy of a production ML feature engineering platform – Venkata Pingali
This talk draws upon the Scribble’s experience in building and evolving a production feature engineering platform, and the many conversations we have had with user data scientists. The talk will focus on the learnings, and not on the Scribble product itself, and expand on the talk from Fifth Elephant Mumbai in Jan 2019 on reducing […]
Watch NowAccelerating ML using Production Feature Engineering Platform by Venkata Pingali
Anecdotally, only 2% of the models developed are productionized, i.e., used day to day to improve business outcomes. Part of the reason is the high cost and complexity of productionization of models. It is estimated to be anywhere from 40 to 80% of the overall work.
Watch NowGlobal Feature Store Meetup #13 – Scribble Data
Feature stores have been traditionally designed for complex ML applications (Big-ML) that normally assume clear and high value propositions, long lead times, skilled staff, and advanced methods. Sub-ML is a space of mid-complexity ML applications where there is higher uncertainty in terms of value, methods used, available staffing, and speed is critical. Sub-ML is interesting […]
Watch NowOperationalizing responsible Machine Learning
ML models have to be both economically viable and FAccT (Fair, Accountable, Transparent). The terminology is new but not the need to defend models or to attest they can be trusted. Such requirements were present from the 70s for credit scoring models. What has changed is the scale and scope.
Watch NowExperimentation in Data Science
The ‘science’ in Data Science refers to the process of developing systematic understanding of the world through observations and experimentation. This science is happening in the context of fast moving organizations, in near realtime, and by folks who have varied backgrounds. The most familiar version of the experimentation is the A/B testing.
Watch NowDevOps for Machine Learning Projects
In this session, Dmitry Pretrov and Ivan Shcheklein – co-founders of DVC – discuss: How software engineering principles apply to Machine Learning development and deployment. How ML systems are different from traditional applications. Importance of data versioning.
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