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Saturday, June 27, 2020

As per oracle Oracle Analytics Cloud:  "Oracle Analytics empowers customers with industry-leading, AI-powered, self-service analytics capabilities for data preparation, visualization, enterprise reporting, augmented analysis, and natural language processing."

Augmented

Applied and invisible—exponentially boosting your effectiveness.

  • Enrich discovery and data sources
  • Recommend new metrics, flows, and sources
  • Identify drivers and influencers of performance
  • Speak to your data with conversational analytics
  • Generate narratives and actions automatically

Integrated

Right place, right time—in your context.

  • Integrate your work, data, and systems
  • Experience a single environment for data prep, visualization, and dashboards
  • Permeate insights continuously across systems
  • Deliver intelligence with context and timeliness
  • Embed at the optimal point of impact

Collaborative

A common foundation for sharing knowledge.

  • Break down walls, allowing all stakeholders to work together
  • Deploy global transformation policies for all to use
  • Monitor, align, and act on business metrics
  • Seamless, transparent, and free of constraints
  • Enable business and IT to deliver on common goals

Monday, May 27, 2019

Python pickle module is used for serializing and de-serializing a Python object structure.Any object in Python can be pickled so that it can be saved on disk. 


  • It  serializes the object first before writing it to file. 
  • It is a way to convert a python object (list, dict, etc.) into a character stream. 
  • It helps to reconstruct the object in another python script.

import pickle
  
def storeData():
    # initializing data to be stored in db
    Omkar = {'key' : 'Omega', 'name' : 'Hello Omega',
    'age' : 99, 'pay' : 40000}
    Jagdish = {'key' : 'Alfa', 'name' : 'Hello Alfa',
    'age' : 55, 'pay' : 50000}
  
    # database
    db = {}
    db['Omega'] = Omega
    db['Alfa'] = Alfa
      
    # Its important to use binary mode
    dbfile = open('examplePickle', 'ab')
      
    # source, destination
    pickle.dump(db, dbfile)                     
    dbfile.close()
  
def loadData():
    # for reading also binary mode is important
    dbfile = open('examplePickle', 'rb')     
    db = pickle.load(dbfile)
    for keys in db:
        print(keys, '=>', db[keys])
    dbfile.close()
  
if __name__ == '__main__':
    storeData()
    loadData()

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