Periscope Data

2012
San Francisco, CA, USA
Nov 25, 2019   |  By Govind Rajagopalan
In a previous post, we learned what Machine Learning (ML) classification problems are, we saw how Naive Bayes was used to solve the classification problem of sentiment analysis — detecting whether text is positive or negative. In this post, we are going to learn about Support Vector Machines (SVM), another popular technique used for classification problems.
Nov 22, 2019   |  By Scott Castle
Do you make guesses about how users are engaging with your product? Before we had the ability to analyze detailed information about usage, we might have observed a few people operating the product and made anecdotally informed guesses about how the user dynamics worked. But in today’s data data-rich environment, we can combine quantitative datasets with a little SQL to practice data-informed product management.
Nov 19, 2019   |  By Amy Lin
If you’re involved in building business intelligence for your organization, you’ve probably had to solve the challenge of getting data from one place to another as a critical step to create a holistic view of your data. Unifying various data sources is a daunting task that requires many hours of effort from data teams to build and maintain. That valuable time could otherwise be spent on higher-value problems like transforming raw data from your warehouse into actionable insights.
Nov 13, 2019   |  By Govind Rajagopalan
Machine learning (ML) refers to the use of existing data, computing power, and effective algorithms to identify patterns in data, recognize those patterns when they occur again, and correctly predict an outcome based on those patterns. A frequent type of problem encountered in machine learning is the classification problem. In these problems, we attempt to predict whether an object or an event belongs to a certain category.
Oct 11, 2019   |  By Harry Glaser
One of the best parts of building an advanced analytics tool for today’s most data-driven organizations is that our team has a daily opportunity to interact with people who are at the forefront of the modern data revolution. The outstanding data teams at companies like Uber, Tinder, and Oscar Health have used data analysis to turn opportunity into reality in their industries. When we talk about turning data teams into superheroes, these are exactly the people and scenarios we have in mind.
Nov 19, 2018   |  By
Businesses across the globe are rushing to analyze their data and turn insights into competitive advantages. Before you can successfully invest in a data tool, you need to answer a series of important questions. How can you combine the various data sources for a unified analysis? Who will use the platform and what skills do they need? Who will be consuming the data that comes out of these data dives?
Nov 19, 2018   |  By
You already know how valuable data can be for your business, but you might not know exactly which tactics will generate business value from your data. The key is building a data team to help translate every business question into a data-informed decision, so you never act on hunches again.
Sep 16, 2018   |  By
In this guide, you’ll learn some simple tips for creating data analytics infrastructure using SQL. We’ll go through an explanation of some foundational concepts you’ll need to manipulate your data and make it valuable, with useful SQL code examples at every step along the way.
Sep 1, 2018   |  By
Citizen data scientists can bring a lot of new knowledge to the analysis process, but they need to be trained to ensure that they're producing correct conclusions. This guide details steps a team can take to set the stage for analysts from business teams and provide them with the tools and culture they need to succeed.
Aug 1, 2018   |  By
With Periscope Data discovery for business, citizen data scientists from a range of business teams will be given direct access to datasets to look for new insights. To help on this search, the Periscope team has compiled some tips to serve as a guide for the exploration, charting and storytelling process.
Apr 24, 2019   |  By Periscope Data
Learn how our customers use Periscope Data for product management.
Apr 2, 2019   |  By Periscope Data
Whether you’re running queries or running businesses, Periscope Data helps everyone in your company answer complex questions using data.
Jan 14, 2019   |  By Periscope Data
Periscope Data's Harry Glaser presented at the ODSC West Conference in 2018 about data teams and their ethical and moral role in managing AI.
Dec 17, 2018   |  By Periscope Data
There’s a lot of work to do to transform raw data into data-driven decisions. Each company has unique data needs, but there’s a universal need to clarify responsibilities, roles and processes to get the most out of data. Our data-driven panel discusses horizontal vs. vertical workflows, centralized vs. decentralized data teams and generalists vs. specialists.
Dec 17, 2018   |  By Periscope Data
Preparing clean datasets for company-wide use is one of the most crucial roles of any data team. The data needs to be clean, accurate, reliable and easy for other teams to read. Our data-driven panel dives into the programs that they’ve built to create a single source of truth for their company’s data.