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Stardog Appoints Craig Harper as Chief Executive Officer

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Stardog Press Kit

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Articles

Feb 17, 2021

Citizen data scientists are a good thing, but are they the only thing?

“Data rules the world and, as a result, we want data to drive all the big decisions about how the world works because we believe in rationality, evidence, and science. But most organizations struggle to leverage that data to its competitive advantage. It’s probably even accurate to say that, statistically speaking, almost all organizations fail to get this right. So, what do we do about this problem?” See the full article here.

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Articles

Jan 12, 2021

Why Digital Transformation Will Become More Critical in 2021

“Organizations of all sizes have demonstrated unprecedented resilience in light of COVID-19 and have placed an even greater focus and investment on digital transformation. Despite this renewed attention, fundamental data challenges remain a primary obstacle. In 2021, even as we expect the pandemic to come under control, organizations can expect to see further intensification and specialization of the following three technology trends.” Read the full article by CEO Kendall Clark in TDWI.

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Articles

Jan 12, 2021

Turning Data into Knowledge: Three Key Enablers for a Better Data Strategy in 2021

“The mandate for enterprise IT to deliver business value has never been stronger. Today tech professionals are key participants in helping drive enterprise business strategy. Yet, to be truly effective, they are quickly learning that agility is the key enabler. Hampered by data strategies that leave teams flat-footed when the market shifts or new questions arise — and with the enterprise data landscape becoming increasingly hybrid, varied, and changing — the year 2021 will see big shifts in how enterprises pivot from a reactive to a responsive Data Strategy.

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Articles

Jan 6, 2021

Data Fabric Success: Is Query-Answering the Missing Stitch

“Data fabrics are the best way to ensure that digital transformations are successful and rooted in connected data that can be queried no matter its location, based on its business meaning and value to the enterprise. Whatever else we can say about 2020, it’s been a transitional year in terms of enterprise data management and digital strategy. The unprecedented crises that we’ve all faced put a renewed focus on digital transformation and data management.

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Press Releases

Jan 6, 2021

Stardog Named a Data Fabric Sample Vendor in Gartner Hype Cycle for Supply Chain Planning Technologies, 2020

ARLINGTON, VA., January 6, 2021 – Stardog, the leading Enterprise Knowledge Graph (EKG) platform provider, today announced that Gartner, Inc., a leading IT research and advisory firm, has recognized the Company as a data fabric sample vendor in its 2020 Hype Cycle for Supply Chain Planning Technologies. According to the report, “Advanced data fabrics have the capability to assist with graph data modeling capabilities (which is useful to preserve the context of the data along with its complex relationships), and allow the business to enrich the models with agreed upon semantics.

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Articles

Jan 5, 2021

Knowledge graphs power the FAANG companies, you can leverage them too

“People talk about “the FAANG companies” (aka Facebook, Apple, Amazon, Netflix, and Google) as a coherent group, even though they’re each very different sorts of businesses with mostly non-overlapping customers and value propositions. However, one thing they share is they are among the most valuable companies on the planet. But what if they share more than just size?” Read the full article by CEO Kendall Clark on Digitizing Polaris.

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Articles

Dec 22, 2020

Big Data Industry Predictions for 2021

“While data continues to rule the world, organizations are still finding themselves struggling to leverage that data for a true competitive advantage. The Citizen Data Science Movement has emerged to widely promote the ability to manipulate and interpret data. But is there is a better way? Wouldn’t it be smarter (and easier) to simply bring business meaning to the data and repair the data rather than fix the people given that raw uninterpreted data located somewhere in a system isn’t very helpful.

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