Goldman Sachs uses Forward Enterprise to model entire 15,000+ device network

How does Goldman Sachs perform end-to-end path analysis, and proactively ensure that network behavior is aligned with stated policies and intent? They use Forward Enterprise for network modeling and network verification. With Forward, Goldman Sachs has significantly improved operational efficiency and successfully reduced change-related incidents.

Read why a Fortune 50 financial services company calls Forward Enterprise a critical component of their infrastructure automation, and how their network engineering team relies on the Forward platform as the single source of truth for their network

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The Changing Landscape of B2B Commerce

B2B Commerce is quickly evolving, with customers expecting more, but the technology has drastically improved, making delivering on such expectations simpler. Learn how to leverage best practices and modern technology to make your B2B eCommerce website fresh and relevant for your customers today.

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Flatfile For Data Onboarding – Webinar

B2B software can't move forward without customer data. Getting that data into a software product, however, is critical for customers to understand the true value of an application.

A reliable, intuitive data onboarding solution helps companies deliver an exceptional customer experience when it matters most – minutes after signing up for a product. This ensures that customer data is imported quickly, without errors, allowing the customer to see the true value of what they signed up for.

Flatfile is leading innovation in data onboarding, with two B2B products that solve this critical pain-point for companies with machine-learning, intuitive UX experiences, and an unmatched drive to automate data onboarding – without sacrificing data quality, and security.

Interested in how Flatfile can help your company?

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Flatfile For Data Onboarding

Data onboarding, the process of migrating critical B2B data between systems, or importing directly from customers, has been neglected from true innovation.

Companies from startups all the way through enterprise operations struggle with data onboarding. Patchworks solutions include: using CSV templates, creating custom scripts to handle complex import flows, or simply hiring expensive services teams to manually onboard data.

Flatfile is leading innovation in data onboarding, with two B2B products that solve this critical pain-point for companies with machine-learning, intuitive UX experiences, and an unmatched drive to automate data onboarding – without sacrificing data quality, and security.

Interested in how Flatfile can help your company?

Get Whitepaper

The State of Data Onboarding

B2B software can't move forward without customer data. This process, known as data onboarding, has the potential to directly affect the value a customer sees in a product. A critical stage during the customer onboarding journey, data onboarding tasks product and engineering teams with ensuring every onboarding touchpoint is intuitive, and optimized.

However, data onboarding has been largely isolated from true innovation. Enter Flatfile.

In this report, we explore Flatfile's research compiled with data onboarding survey results, the challenges B2B companies are facing when it comes to migrating customer data and finally, what they are doing to overcome them.

Get Whitepaper

Flatfile For Data Onboarding – Webinar

B2B software can't move forward without customer data. Getting that data into a software product, however, is critical for customers to understand the true value of an application.

A reliable, intuitive data onboarding solution helps companies deliver an exceptional customer experience when it matters most – minutes after signing up for a product. This ensures that customer data is imported quickly, without errors, allowing the customer to see the true value of what they signed up for.

Flatfile is leading innovation in data onboarding, with two B2B products that solve this critical pain-point for companies with machine-learning, intuitive UX experiences, and an unmatched drive to automate data onboarding – without sacrificing data quality, and security.

Interested in how Flatfile can help your company?

View Now

Flatfile For Data Onboarding

Data onboarding, the process of migrating critical B2B data between systems, or importing directly from customers, has been neglected from true innovation.

Companies from startups all the way through enterprise operations struggle with data onboarding. Patchworks solutions include: using CSV templates, creating custom scripts to handle complex import flows, or simply hiring expensive services teams to manually onboard data.

Flatfile is leading innovation in data onboarding, with two B2B products that solve this critical pain-point for companies with machine-learning, intuitive UX experiences, and an unmatched drive to automate data onboarding – without sacrificing data quality, and security.

Interested in how Flatfile can help your company?

Get Whitepaper

The State of Data Onboarding

B2B software can't move forward without customer data. This process, known as data onboarding, has the potential to directly affect the value a customer sees in a product. A critical stage during the customer onboarding journey, data onboarding tasks product and engineering teams with ensuring every onboarding touchpoint is intuitive, and optimized.

However, data onboarding has been largely isolated from true innovation. Enter Flatfile.

In this report, we explore Flatfile's research compiled with data onboarding survey results, the challenges B2B companies are facing when it comes to migrating customer data and finally, what they are doing to overcome them.

Get Whitepaper

Flatfile For Data Onboarding – Webinar

B2B software can't move forward without customer data. Getting that data into a software product, however, is critical for customers to understand the true value of an application.

A reliable, intuitive data onboarding solution helps companies deliver an exceptional customer experience when it matters most – minutes after signing up for a product. This ensures that customer data is imported quickly, without errors, allowing the customer to see the true value of what they signed up for.

Flatfile is leading innovation in data onboarding, with two B2B products that solve this critical pain-point for companies with machine-learning, intuitive UX experiences, and an unmatched drive to automate data onboarding – without sacrificing data quality, and security.

Interested in how Flatfile can help your company?

View Now

Flatfile For Data Onboarding

Data onboarding, the process of migrating critical B2B data between systems, or importing directly from customers, has been neglected from true innovation.

Companies from startups all the way through enterprise operations struggle with data onboarding. Patchworks solutions include: using CSV templates, creating custom scripts to handle complex import flows, or simply hiring expensive services teams to manually onboard data.

Flatfile is leading innovation in data onboarding, with two B2B products that solve this critical pain-point for companies with machine-learning, intuitive UX experiences, and an unmatched drive to automate data onboarding – without sacrificing data quality, and security.

Interested in how Flatfile can help your company?

Get Whitepaper

The State of Data Onboarding

B2B software can't move forward without customer data. This process, known as data onboarding, has the potential to directly affect the value a customer sees in a product. A critical stage during the customer onboarding journey, data onboarding tasks product and engineering teams with ensuring every onboarding touchpoint is intuitive, and optimized.

However, data onboarding has been largely isolated from true innovation. Enter Flatfile.

In this report, we explore Flatfile's research compiled with data onboarding survey results, the challenges B2B companies are facing when it comes to migrating customer data and finally, what they are doing to overcome them.

Get Whitepaper

The Innovator’s Guide to Strategic DAM Replacement or Consolidation

In the most forward-looking and successful companies, DAM is no longer just about marketing. Rich-media assets are now recognized as a foundational component of the digital supply chain that stretches across the whole enterprise. Content itself is becoming more ephemeral in nature.

Handcrafting each new asset from scratch as an individual work of art is being replaced by increased reuse of assets, and a rise in system-generated assets. Video has become mainstream and new types of online media types are emerging, such as 3D models, virtual and augmented reality, and even holography.

As business requirements change and new challenges emerge, your traditional Digital Asset Management system is probably at its breaking point or has been circumvented by various ad-hoc workarounds. Without taking action, the value of your assets will remain locked in isolated systems, where they will wither away, rather than making a measurable contribution to business growth. It’s time to step into the future.

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7 Ways to Accelerate Products to Market

This guide, created for managers and executives at product-driven companies, answers three main questions:

  • How does accelerating product introduction grow market share in an era of market disruption?
  • What opportunities for acceleration exist throughout the product design, development, and go-to-market process?
  • Why do many efforts to streamline and accelerate product development fail to deliver real results — and what is required for success?

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B2B Commerce New Solution Checklist

Online B2B Commerce is evolving quickly, and if you haven't researched your options in awhile, there may be lots of capabilities that have become available since your last software investment. This checklist will guide you through various topics to help you determine what your next solution needs to support, and help you know which topics to ask about during your research!

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Query Optimization

This article explores using a simple example problem of finding unique column values in a moderately large data set. As is often the case in analogous real-world problems, the column of interest will have relatively few unique values, compared with the number of rows in the table. There are two parts to this analysis: creating the sample data, and writing the distinct-values query itself.

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