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Posts about Business Analytics

Trifacta for Marketers: Driving Marketing Analytics

This is the second post in a series about how marketers are leveraging Trifacta, following our first post on onboarding marketing data. In this post, we discuss how Trifacta is being used to prepare data for marketing analytics. When presenting marketing findings, one of the first things asked is “How accurate is the data?” When […]

Trifacta  |  April 30, 2020

Trifacta for Marketers: Accelerating Marketing Data Onboarding

This is the first post in a series about how marketers are leveraging Trifacta Data Engineering Cloud. In this post, we discuss how Trifacta is being used for marketing data onboarding. In recent years, nothing has endured quite like data-driven marketing—using data effectively has become the status quo for modern marketers, and that expectation is […]

Trifacta  |  April 24, 2020

The “Goldilocks” Solution to Integrating Unfamiliar Client Data

Let’s say you work for an analytics provider. It could be a marketing analytics provider, healthcare, supply chain—it doesn’t matter. You’ve just closed a deal with a new client. One of your first orders of business is to get your hands on your client’s data.  Your client sets up data sharing. Your team stands ready […]

David McNamara  |  April 6, 2020

Integrating Unfamiliar Data: Trifacta vs. Excel for Analytics Providers

The Challenge Your company provides analytics as a service to your customers. Each time you bring on a new client, it kicks off the process of gathering the client’s data, getting to know the formats and accessing the contents of the data, preparing that data for analysis by cleaning and standardizing problem areas, validating the […]

David McNamara  |  March 24, 2020

Democratization for Speed

Data Prep Democratization = SPEED The reality for most professionals working on advanced analytics or data modernization projects is that they are faced with a myriad of challenges that span beyond the actual project work they are responsible for (e.g. Data Scientists working on improving the actual AI algorithms). To address this challenge, organizations are […]

Brian Shealey  |  January 31, 2020

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The Opportunity to Drive AI Initiatives with the U.S. Department of Health and Human Services and Beyond

This past month, the U.S. Department of Health and Human Services (HHS) announced the awardees selected to provide Intelligent Automation/Artificial Intelligence (IAAI) solutions, services and products to the agency through their Program Support Center (PSC). As the leader of our U.S. public sector operations, I am happy to share that Trifacta is one of the […]

Ron Ziegler  |  June 21, 2019

How IN-RGY Implemented Trifacta on AWS to Help Payment Processing Provider Wrangle Data 70% Faster

Automation is the growing focus of many organizations. Taking processes that have been traditionally done manually and automating them frees up time for analysts to be proactive in decision making and become more efficient. At the end of 2018, Trifacta’s partner IN-RGY had one of their clients approach them with an initiative to standardize all […]

Matt Derda  |  June 18, 2019

How Malwarebytes Uses Trifacta on an AWS Data Lake to Scale Marketing Intelligence

  Marketing and lead generation is a critical aspect for every company. But collecting, enriching, and maintaining information on leads and customers requires a lot of time and effort – especially as your business scales. Sean Ma, Director of Product Management Trifacta, and Manjunath Vasishta, Director of Data Science and Engineering at Malwarebytes,  discuss how […]

Matt Derda  |  June 14, 2019

7 Ways Data Enrichment Boosts Your Business

Data is the lifeblood of contemporary businesses and is used to formulate marketing, sales and customer service strategies. It is at the core of every decision business leaders make to promote the growth and profitability of their organizations. Data empowers leaders to make precise decisions based on facts and trends rather than speculations. Excellent business […]

Paige Schaefer  |  May 11, 2019

Rethinking Your Team’s Roles & Responsibilities to Drive Data Prep Success

All data initiatives, whether machine learning, visualization or reporting, rely on clean data. Which means that data preparation is essential to any data-driven organization. Increasingly, organizations are adopting new solutions to increase the accessibility of data preparation (and reduce the time involved) in a governed, secure manner—no longer is data preparation considered a job for […]

Megan Kierstead  |  October 29, 2018

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Commit to Clean Data: Ensure Transparency

We’ve covered a lot of ground in our Clean Data Manifesto series, outlining the 5 tenets of clean data. We’ve reviewed the reasons you should prioritize and set targets, identify issues early and often in your data preparation efforts, why collaboration is the key to strengthening these efforts, and why it’s important to constantly monitor […]

Adam Wilson  |  September 12, 2018

Commit to Clean Data: Constantly Monitor

If you follow our blog, then by now you’re probably well aware of our Clean Data Manifesto, the tenets of clean data that we’ve identified, and how they help inform sound data preparation practices. We’ve reviewed the reasons why you should prioritize and set targets, identify issues early and often in your data preparation efforts, […]

Adam Wilson  |  August 29, 2018

Commit to Clean Data: Collaborative Curation

At Trifacta, we’re committed to clean data. That’s why we created the Clean Data Manifesto, which is focused on this commitment and anchored by our five tenets of proper data preparation. I’ve walked through the first two tenets in my last two blog posts—the first, focused on prioritizing and setting targets, and the second, about […]

Adam Wilson  |  August 20, 2018

Commit to Clean Data: Identify Issues Early and Often

Last week on our blog, I introduced the Clean Data Manifesto, the call to action we have developed for anyone who works with data. The manifesto is about committing to clean data—which is critical to being able to stand behind the validity of any analysis. As part of this project, we have identified five tenets […]

Adam Wilson  |  August 6, 2018

Commit to Clean Data: Prioritizing & Setting Targets

Of all the ways you can spend your time as an analyst—especially up to 80 percent of your time—the janitorial work of preparing data isn’t a favorite for most people. It has historically been a manual task: monotonous, time consuming and not particularly enjoyable. But as most analysts have experienced in one way or another, […]

Adam Wilson  |  July 30, 2018

Wrangling Census Data to Predict the Location of Amazon HQ2

Last fall Amazon announced its search for a second headquarters, considering applications from a whopping 200 cities. Now, those initial 200 have been narrowed down to 20 “Amazon HQ2” hopefuls that span the country and include one Canadian city, Toronto. For these shortlisted cities, there is a lot at stake—the winning city stands to gain […]

Vijay Balasubramaniam  |  July 12, 2018

Data Preparation – Who Needs It, Why Now, and How do I Build a Business Case?

By Stewart Bond, IDC Research Director, Data Integration and Data Integrity Software It’s a new world we live and work in. In recent years we have seen dramatic changes in distributed computing, combined with a massive increase of data volume, variety, and velocity as big data fuels digital transformation. In parallel, exponential increases in computing […]

Stewart Bond  |  June 14, 2018

The Importance of Data Wrangling for Machine Learning

To businesses across every industry, machine learning and artificial intelligence have the potential to drive huge benefits. But what does it look like to implement a machine learning initiative in practice, and what are the pitfalls that organizations often run into along the way? To the latter question, Harvard Business Review has a clear answer: […]

André Balleyguier  |  April 10, 2018