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Published By: Stardog Union     Published Date: Jul 27, 2018
When enterprises consider the benefits of data analysis, what's often overlooked is the challenge of data variety, and that most successful outcomes are driven by it. Yet businesses are still struggling with how to query distributed, heterogeneous data using a unified data model. Fortunately, Knowledge Graphs provide a schema flexible solution based on modular, extensible data models that evolve over time to create a truly unified solution. How is this possible? Download and discover: • Why businesses should organize information using nodes and edges instead of rows, columns and tables • Why schema free and schema rigid solutions eventually prove to be impractical • The three categories of data diversity including semantic and structural variety
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Stardog Union
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
Analysts struggle to incorporate new sources of data into their analysis because they rely on Microsoft Excel or other tools that were not designed for data blending. Deleting columns, parsing data, and writing complicated formulas to clean and combine data every time it changes is not an efficient way for today’s analysts to spend their time. Download The Definitive Guide to Data Blending and: Understand how analysts are empowered through data blending Learn how to automate time-consuming, manual data preparation tasks Gain deeper business insights in hours, not the weeks typical of traditional approaches
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Alteryx, Inc.
Published By: AstuteIT_ABM_EMEA     Published Date: Feb 02, 2018
MongoDB is an open-source, document database designed with both scalability and developer agility in mind. MongoDB bridges the gap between key-value stores, which are fast and scalable, and relational databases, which have rich functionality. Instead of storing data in rows and columns as one would with a relational database, MongoDB stores JSON documents with dynamic schemas. Customers should consider three primary factors when evaluating databases: technological fit, cost, and topline implications. MongoDB's flexible and scalable data model, robust feature set, and high-performance, high-availability architecture make it suitable for a wide range of database use cases. Given that in many cases relational databases may also be a technological fit, it is helpful to consider the relative costs of each solution when evaluating which database to adopt.
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total, cost, ownership, comparison, mongodb, oracle
    
AstuteIT_ABM_EMEA
Published By: SAP     Published Date: Jul 17, 2012
Relational database management systems (RDBMSs) are systems of software that manage databases as structured sets of tables containing rows and columns with references to one another through key values. They include the ability to optimize storage, process transactions, perform queries, and preserve the integrity of data structures. When used with applications, they provide the beating heart of the collection of business functions supported by those applications. They vary considerably in terms of the factors that impact the total cost of running a database application, yet users seldom perform a disciplined procedure to calculate such costs. Most users choose instead to remain with a single vendor's RDBMS and never visit the question of ongoing hardware, software, and staffing fees.
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sap, infrastructure, database, data management, white paper, management, storage, business functions, data integration, business technology
    
SAP
Published By: Calpont     Published Date: Mar 13, 2012
In this white paper you will find insight as to how the Calpont InfiniDB database performs far beyond the abilities of a row-based database.
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data warehouse, warehouse, benhcmark, infinidb, calpont, row-based, warehouse, mpp, parallel processing, columns, rows, column, row, data management
    
Calpont
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