According to Forrester, one-third of companies are commercializing or sharing their data for revenue.* Unilog, a global technology company, is an example of one company who successfully monetized upstream manufacturing by enriching, cleaning and joining data needed by its customers – using Paxata’s data preparation solution.
Join us for a 30-minute webcast on Tuesday, February 27 at 11:00 am PST | 2:00 pm EST to learn how Paxata helped Unilog to:
- Reduce duplicate data identification time from 4 hours to 10 minutes
- Increase rate at which enriched data can be brought into the marketplace
- Generate direct revenue via a service that matches customer’s product data against Unilog’s rich catalog
Noah Kays, Director of Content Subscriptions, Unilog
Farnaz Erfan, Senior Director, Product Marketing and Strategy, Paxata
Organizations today are coping with two major obstacles as it relates to data preparation and data quality: significant data variety and a complex mix of data types.
Rapid data profiling (RDP) capabilities are becoming available to increase time spent on value-added analytics activities. RDP gives first eyes on data and the ability for business users to onboard, profile, and create quality information in minutes.
During this event for business intelligence, analytics, and IT architect professionals, we will provide viewers with:
- Summary of RDP and key benefits
- Use cases where RDP has significant impact
- A short demo of Paxata’s innovative, point-and-click approach for streamlining your data profiling and remediation efforts.
A majority of big data initiatives fail to deliver business value. If you are getting started with building an enterprise data lake on Azure – or have an existing data lake – and want to ensure your business analysts can quickly and easily access and interact with your data, this webcast is a must.
Join us to understand how to accelerate value from your Azure data lake using self-service data preparation. You’ll learn the top techniques to turn raw data into ready information in a matter of hours, not months.
During this 30-minute webcast, designed for business intelligence, analytics, and IT architect professionals, our presenters will provide:
- A set of steps for unlocking business value from your data lake and quickly deliver analytical insights
- A brief demo showing the ease of use to empower analysts to interactively browse, explore, and prepare data in the data lake stores and utilize within Power BI
Paxata’s Adaptive Workload Management – new in Fall 2018 – is designed to give organizations the freedom of choice in right-sizing their data volumes for interactive data prep vs. repeated, batch workloads.
This release also provides an elastic resource allocation service on a number of orchestration frameworks including Kubernetes, Cloudera and Hortonworks YARN, Amazon EMR, and Microsoft Azure HDInsight, offering dynamic scaling of large data prep workloads across ephemeral clusters to lower cost and improve performance.
Join us for this 30 minute webcast to see a brief demo of our Fall 2018 release and learn how to:
- Define your own interactive data size
- Use progressive loading to jumpstart your data preparation
- Dynamically allocate batch resources to lower costs
- Accelerate your data prep projects with Paxata
Technology disruption such as distributed compute (Cloud), Internet of Things (IoT), Big Data, and Artificial Intelligence opens new worlds of digital transformation for enterprises across all industries. Data is at the heart of every one of these initiatives and provides the fuel for making every person, process, and system more intelligent and efficient. We have reached the tipping point where all businesses recognize they cannot compete in a digital age using analog-era legacy data solutions and architectures. The winners in the next phase of business will be those enterprises that obtain a clear handle on the foundations of modern data management fabric.
The modern big data fabric helps enterprise organization accelerate insights by automating ingestion, curation, discovery, preparation, and integration from data silos. According to Forrester, the benefits of investing in big data fabric are higher quality data and consistency, reduced IT costs, and greater agility to meet business demands. But it comes with some challenges.
Join Noel Yuhanna from Forrester and Paxata’s Nenshad Bardoliwalla as they discuss:
- Latest trends, benefits, and use cases of big data fabric
- Challenges enterprise organizations must overcome
- How to deliver faster time-to-value with enterprise grade self-service big data fabric
On average, eight out of every ten hours spent on analytics and data science projects goes into discovering, cleaning, and shaping data instead of using that data to find actionable insights. In this webinar, learn how Paxata, an AWS Machine Learning Competency Partner, and Amazon Web Services (AWS) accelerate the data preparation parts of any data-centric projects.
Discover how Paxata Self-Service Data Prep for AWS delivers a visual and intuitive data preparation experience for data analysts, data scientists, and business subject matter experts to help them explore, profile, and transform data for analytics. You’ll hear how Paxata’s built-in machine learning algorithms identify joins, overlaps, and anomalies that clean and match data to accelerate data preparation for analytics projects.
Join our webinar to learn
- Reduce data preparation from 80% of a project’s time to 20%.
- Accelerate data science and analytics projects.
- Leverage built-in machine learning algorithms to clean and shape data for your data science initiatives.