Come As You Are (aka no ETL required)
Knowi’s nifty natural language and machine learning capabilities mean we just may have stumbled upon the answer to everyone’s dreams and one that supersedes the ETL relic of old.
The Six Steps of Creating a Machine Learning Model in Knowi
Creating a Classification Model for Breast Cancer Screening The UCI Machine Learning Repository contains many full data sets that can be used to test and train machine learning models. One such example is the Breast Cancer Wisconsin (Diagnostic) Data Set which relates whether breast cancer is benign or malignant to 10 specific aspects of the …
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5 Smart Takeaways from Our Webinar with Skratch
Curious to see how mobile application development company, Skratch, is making sense of silo’d data with augmented analytics technology? Scott Bennet, CEO of Skratch, and Ronen Akiva, CTO of Skratch, share how they are benefiting – and growing their business – from data-driven decisions. Here are 5 smart takeaways about Knowi from our webinar with …
Native Analytics on MongoDB Atlas – Tutorial
This is a 10 minute, hands-on tutorial of setting up connectivity to MongoDB Atlas and building visualizations from it using Knowi. The end result is a dashboard of restaurants near the NYC area. In a previous post, we reviewed MongoDB Atlas. CONNECTING This assumes that you have an Atlas account setup. If you don’t, go …
Add Predictive Analytics on Your Dataset in 3 Steps
Knowi Predictive Analytics brings machine learning capabilities to every Data Engineer. Integrate machine learning into your analytics workflows and drive data directed actions. The platform provides two options: Out-of-the-box predictive analytics capabilities that test a dataset against a variety of forecasting models to determine the model best suited to the data, with the least Sum …
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Augmented Analytics: What It Is and Why You Need It
You hear it everywhere that business teams are hungry for analytics. They crave accurate predictions and forecasts to allow them to make better business decisions, faster. The problem is data has become so complex that most of the time they have to wait for it to be analyzed and presented. They waste time waiting and …
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Tableau and MongoDB Analytics: Why It’s a Bad Marriage
The Challenges of MongoDB Analytics (or any other NoSQL analytics) with Tableau First off, we are not here to bash Tableau. Tableau is an excellent analytics tool for structured relational data. Our point here is that data has moved beyond well-understood structured data and now includes semi-structured and unstructured data stored in newer NoSQL databases, …
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How Boku Successfully Transitioned to a Data-Driven Enterprise Using Knowi
We had a chance to sit down with our friends at Boku recently and talk about how they are using Knowi to provide business analytics across all their teams, including product, accounts, and business development, and have recently extended their analytics as value-added product offerings to their partners and customers. If you are not familiar …
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Will Cockroaches and Data Silos Be the Only Things Left? Part II
Data Services is the Answer! Yes, but… In our last post, we talked about using a data warehouse strategy as one of the ways to break down data silos across multiple departments and systems. Building a data warehouse is a traditional way to tackle the data silo problem. However, successful projects take serious organizational commitment …
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7 Requirements to Deliver Business-Driven Analytics in the Modern Data Age
The journey to modern data has been fast and furious. Within a just a few decades, we have gone from retrospective analytics on operational data located within your four walls to prescriptive analytics using real-time multi-sourced data and everything in between. While data, data storage, and data processing technologies have advanced, I would argue that …
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