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• Java Collections
  ...ever, this approach makes them slower when working on fixed size primitive data types. ...performance equal to O(1). On the other hand, a [[LinkedList]] stores its data as list of elements and every element is linked to its previous and next el
  11 KB (1,665 words) - 12:58, 27 May 2018
• Data Science
  ...ing of Data Warehouses & Big Data. It ensures that the data extracted from data sources remains intact in the target systems as well. *Improve data quality & data governance
  16 KB (2,316 words) - 11:29, 30 May 2018
• QuerySurge
  ...ing of Data Warehouses & Big Data. It ensures that the data extracted from data sources remains intact in the target systems as well. *Improve data quality & data governance
  782 bytes (115 words) - 11:52, 28 May 2018
• Talend Open Studio
  ...lot easier. It also allows big data integration, data quality, and master data management. *It supports extensive data integration transformations and complex process workflows
  761 bytes (109 words) - 11:55, 28 May 2018
• Sisense
  ...isparate datasets, in real-time. It is an ideal tool for preparing complex data for creating dashboards with a wide variety of visualizations. *Unify unrelated data into one centralized place
  913 bytes (133 words) - 11:56, 28 May 2018
• TabLeau
  ...s Desktop, Server, and Online. It is secure, shareable and mobile friendly data warehouse solution. *Connect to any data source securely on-premise or in the cloud
  764 bytes (109 words) - 11:56, 28 May 2018
• MicroStrategy
  *Support for advanced analytics and big data
  658 bytes (82 words) - 11:57, 28 May 2018
• Management Information Systems
  ...le. SAFe is based on Lean and Agile principles and tackles tough issues in big organizations, like architecture, integration, funding, and roles at scale. ...ponent is developed in parallel. The phases in RAD are: business modeling, data modeling, process modeling, application generation, and testing and turnove
  64 KB (10,379 words) - 02:07, 1 June 2018
• Other Practices in Agile
  ...le. SAFe is based on Lean and Agile principles and tackles tough issues in big organizations, like architecture, integration, funding, and roles at scale. ...ponent is developed in parallel. The phases in RAD are: business modeling, data modeling, process modeling, application generation, and testing and turnove
  3 KB (389 words) - 17:04, 28 May 2018
• DevOps
  ...[[lean manufacturing]], to improve the cycle time of extracting value from data analytics. ...erations in cloud environments (i.e., [[data transfer]] or [[Cloud storage|data storage]]). In addition, ResOps also focuses on the optimisation of researc
  14 KB (1,897 words) - 09:25, 31 May 2018
• Collections
  All the operations that you perform on a data such as searching, sorting, insertion, manipulation, deletion etc. can be p ...List and LinkedList?''' ArrayList is an index based, but LinkedList stores data as list of nodes. Insertion, addition or removal of an element is faster in
  9 KB (1,458 words) - 04:16, 5 November 2018
• Java 9
  The second big benefit – it makes the Java Platform more lightweight and more scalable. ...e language and then executing it. Improvements in this area are one of the big advantages of Java 9.
  9 KB (1,352 words) - 04:14, 7 June 2018
• Agile Methodology
  ...le. SAFe is based on Lean and Agile principles and tackles tough issues in big organizations, like architecture, integration, funding, and roles at scale. ...ponent is developed in parallel. The phases in RAD are: business modeling, data modeling, process modeling, application generation, and testing and turnove
  19 KB (2,977 words) - 14:52, 28 June 2018
• Agile/Scrum/Kanban/XP/Waterfall
  ...le. SAFe is based on Lean and Agile principles and tackles tough issues in big organizations, like architecture, integration, funding, and roles at scale. ...ponent is developed in parallel. The phases in RAD are: business modeling, data modeling, process modeling, application generation, and testing and turnove
  64 KB (10,377 words) - 14:41, 28 June 2018
• Big O Notation
  ==What on earth is Big O?== ...it’s dealing with. Big O is a way of measuring how an algorithm scales. Big O references how complex an algorithm is.
  9 KB (1,569 words) - 08:28, 1 August 2018
• Apache Kafka
  ...large volume of data and the second challenge is to analyze the collected data. To overcome those challenges, you must need a messaging system. ...ing data from one application to another, so the applications can focus on data, but not worry about how to share it. Distributed messaging is based on the
  33 KB (5,064 words) - 20:43, 1 December 2018
• TENSORFLOW
  ...developing, testing, and training on a single machine, enabling individual data scientists to: * Quickly download 1,500+ [[Python]]/[[R]] data science packages
  5 KB (618 words) - 10:54, 16 November 2019
• Git-flow
  Allow for minor bug fixes and preparing meta-data for a release Finishing a release is one of the big steps in git branching. It performs several actions:
  11 KB (1,571 words) - 16:01, 12 April 2020