Cambridge Semantics' Top 10 Blogposts of 2018

Posted by Kirk Newell on Dec 19, 2018 2:06:00 PM
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As we wind down 2018 (the Year of the Graph!), we thought we would take a look back on our most popular blogposts this year. So, without further ado, here are the top 10 most popular blogposts of 2018.

10. Data Warehouse vs Data Lake: Understanding the Evolution

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This blogpost is the first of a two-part series written by Sean Martin, our co-founder and CTO, to explain the move from the ubiquitous data warehouses of the past few decades to the rapid build out of data lakes. Read it here.

9. Why a Semantic Layer Over Hadoop Makes Sense

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Organizations today view their data assets as key business drivers for competitive advantage. However, the cost of running analytic solutions is drastically increasing and speed-to-deployment remains a major challenge. Businesses know that they have vast amounts of data assets available across a strata of resources, but can have difficulty drawing any meaningful insights from these resources. That is where the semantic layer comes in. Read the blogpost here.

8. [Slideshare] The Year of the Graph

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In his presentation to a packed house at Gartner's Data & Analytics Summit 2018, Cambridge Semantics' VP of Solution Engineering, Ben Szekely, discussed why 2018 is the "Year of the Graph" and how Anzo® utilizes graph database technology to provide a semantic layer for your data lake. These are the slides from that presentation. View them here.

7. Thomson Reuters, Graph-Based Data Analytics and Serendipity

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In this blogpost, we discussed some of the news to come out of the EDM Council’s Members Brief, attended by 400 or so financial data professionals. We were honored to be recognized for our support of their knowledge graph initiatives and shared a recent article in the International Business Times by our founder and CTO, Sean Martin, about the broader industry significance of Thomson Reuters’ introduction of enterprise graph analytics for its customers. Read the blogpost here.

6. FIBO, FIBO, It's Off to Work We Go

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In this blogpost, originally written in 2016, we discuss a joint project between State Street, The EDM Council, Dun & Bradstreet, Wells Fargo and Cambridge Semantics to to harmonize State Street's Interest Rate Swap data with Dun & Bradstreet's entity hierarchy data using the Financial Industry Business Ontology (FIBO) and Cambridge Semantics' Anzo. Read the blogpost here.

5. What Is a Graph Database?

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2018 has been touted as "The Year of the Graph" as more and more organizations both large and small have recently begun to invest in graph database technology as they look to draw insights and meaning from existing data resources to streamline their operations. But what exactly is a graph database, and how exactly does it provide meaningful insights into the relationships between your data? Find out here.

4. Understanding Graph Databases

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The description of graph databases that you get when you Google it are mostly academic with a lot of descriptions that talk about Leonhard Euler and the seven bridges in Königsberg or Tim Berners-Lee, the inventor of the internet. These theories and visions are fine, but it’s important to lead with the relevance of graph databases or, in other words, "Why are graph databases important to you?" Read the blogpost here to find out.

3. Why Should Businesses Care About Amazon's Neptune Announcement?

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In this blogpost Alok Prasad, President of AnzoGraph, responds to the Amazon Neptune announcement and notes it is just the latest acknowledgment of the mainstream adoption of graph technology and the value it provides over other types of databases. Global brands are realizing that to create a true “Enterprise Data Fabric” they need to invest in open standards-based semantic platforms that can leverage their existing IT & data investments. Read the blogpost here.

2. Welcome to the Semantic – or ‘Smart’ – Data Lake Revolution

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This blogpost by Sean Martin is the sequel to Data Warehouse vs Data Lake: Understanding the Evolution and continues the discussion of the evolution of data management systems. In part one, he discussed two of the most common constructions, data warehouses and data lakes, while in this blogpost he introduces the idea and additional benefits of building data lakes using semantic technology. Read the blogpost here.

1. Creating a Successful Enterprise Knowledge Graph

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Ever since Google mainstreamed knowledge graphs in 2012 through a popular blog on enhanced web search, enterprises have realized that the technologies that make web searches smarter can also be used to create Enterprise Knowledge Graphs for more effective data interlinking and searching. In this blogpost, Partha Sarathi Bhattacharjee, Senior Solution Engineer, explains what an Enterprise Knowledge Graph is and best practices for creating and implementing one at your organization. Read the blogpost here.

Tags: Semantic Layer, Graph Database, Data Warehouse, Smart Data Lake, FIBO, Data Lake, Data Fabric, Knowledge Graph

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