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words of caution in working with artificial neural networks (ANNs)

artificial intelligence on deep learning and, 2nd examples of architectures technique

Australian Square Kilometre Array Pathfinder (ASKAP) AWS, 2nd

Azure, 2nd, 3rd, 4th Banko, Michele batch jobs Beam (Apache) Bezos, Jeff big data

applications of business analytics artificial intelligence (AI) and, 2nd black box models from

cloud computing, 2nd, 3rd concept of

consumer activity

content generation and self-publishing customer journey data, value of

data-driven approaches analysis

data insights

developments towards start of

disk storage and RAM, plummeting cost of ecosystem, 2nd

forming strategy for kick-off meeting programme team scoping meetings growth, for two reasons importance of

improving analytic techniques key roles in

machine data and IoT new way of thinking about new ways to using

open-source software

as organizations’ digital transformation processing power, plummeting cost of

proliferation of devices, generating digital data

reasons for discussing as hot topic role in medical research

role models

scientific research

solution, choosing technologies for storage

story of

as unstructured data using to guide strategy

collecting the data competitors

external factors

own service and product using the data

see also data; technologies, choosing Bitbucket

black-box model from big data Bork, Robert Brill, Eric budget holders

‘build vs. buy’ decision Bumblehive (data centre) business analysts, 2nd business expertise

business intelligence (BI) teams business units

C++

Caffe

cancer research (case study) CapEx, 2nd

cart abandonment Cassandra

central processing unit (CPU) churn reduction

Cisco

Visual Networking Index™

cloud computing, 2nd benefits of

choosing technology clustering

code distribution collaborative filtering

competitors CompStat system

computer storage, types of Comscore

concurrency consumer activity content-based filtering

content generation and self-publishing conversion rate optimization (CRO) convolutional neural networks (CNNs) copyrights

corporate strategies costs

of cloud computing of disk storage of processing power of RAM

saving, 2nd

critical intervention Critical Path Software cross-validation

customer data

applying basic analysis and machine learning to linking

using

customer journey data segmentation criteria value of

customer lifetime value (CLV) customer loyalty

customer segments

customer support, interactions with D3.js

damage control dark data

data

additional quantities of additional types of and analytics roles collection of

moving and cleaning

primary concerns for securing and governing data-driven organization

asking questions about business challenging basic assumptions creating and monitoring KPIs getting new ideas

organizing the data data engineers

data governance

data initiative programme team analytic expertise

business expertise strategic expertise technical expertise data insights

data lakes, 2nd data privacy data protection

Data Protection Directive of 1995 data science

agile analytics algorithms

analytic software analytic tools analytics, types of

artificial intelligence and machine learning black boxes, 2nd

implementing key roles in models

and privacy revelations utilizing within organization data scientists

data silo

data team, recruiting data warehouses, 2nd databases

choosing

document-oriented databases graph databases

key-value stores relational databases search engine databases wide column stores db-engines.com, 2nd Deep Blue, 2nd, 3rd

deep learning

artificial neural networks (ANNs) and, 2nd problems with

DeepMind

demand and revenue Deming, W. Edward descriptive analytics diagnostic analytics differential privacy

digital platforms, visiting disk storage

plummeting cost of distributed computations distributed data storage document-oriented databases eBay, 2nd, 3rd, 4th, 5th

Echo (Amazon)

edge computing. see fog computing Einstein, Albert

Elasticsearch, 2nd

employee job satisfaction end users, 2nd, 3rd, 4th ensemble

ETL (extract, transfer, load) tool EU–US Privacy Shield

exabyte

expert systems Facebook, 2nd fast data, 2nd Fast Works

feature engineering Few, Stephen Flink framework fog computing, 2nd Forbes

forecasting Forrester

Forrester Waves fraud detection

GA360 (Google Analytics’ premium service) Gartner

Gartner Hype Cycle Gartner Magic Quadrants

Gartner’s Analytics Ascendancy Model Gelly, Flink’s

General Data Protection Regulation (GDPR), 2nd, 3rd, 4th General Electric (GE), 2nd, 3rd

General Public License (GPL) genomic data (case study) Geometric Intelligence gigabytes (GB)

GitHub

Glassdoor website Gmail

GNU project Go (game)

goodness-of-fit test

Google, 2nd, 3rd, 4th, 5th, 6th, 7th Google Analytics

Google Cloud, 2nd, 3rd Google Maps

Google ML engine GoogLeNet program

governance and legal compliance data governance

data science and privacy revelations personal data

privacy laws for reporting graph databases

graphical processing units (GPUs), 2nd, 3rd Hadoop (Apache), 2nd, 3rd, 4th, 5th, 6th

Hadoop Distributed Files System (HDFS), 2nd, 3rd hardware, choosing

Harvard Business Review

Higgs boson particle, discovery of high-profile project failure (case study) hiring experts, at scale

hiring process, for lead role aligning with recruitment team finding strong candidates landing the candidate Hive (Apache)

human resources (HR)

IBM, 2nd, 3rd

ImageNet Large Scale Visual Recognition Challenge (ILSVRC) Immelt, Jeff, 2nd, 3rd

Impact Areas for Analytics document Indeed.com

Infrastructure as a Service (IaaS), 2nd, 3rd Instacart

integer programming internet, and publishing Internet Explorer

Internet of Things (IoT), 2nd machine data and

inventory IT cost savings IT teams

Jaklevic, Mary Chris Java

JavaScript job satisfaction JSON format Kafka (Apache) Kasparov, Garry Keras, 2nd

key performance indicators (KPIs), 2nd, 3rd key-value stores

kick-off meeting analytics input business input output

strategic input technical input

KNIME (open source data analytics), 2nd lambda architecture

Laney, Doug

The Large Hadron Collider (LHC), particle physics (case study) latency

lead data scientist lead scoring leadership

ability to deliver results

breadth and depth of technical skills

hiring process for lead role

possession of three unrelated skill sets legal and privacy officers

licenses, for open-source software

LIME (Local Interpretable Model-Agnostic Explanations) tool Linden, Greg

linkage attacks, 2nd Linux

LoRaWAN (Long Range Wide Area Network) machine data and IoT

machine learning (ML), 2nd artificial intelligence and engineers

methods, 2nd, 3rd MacLaurin, Ian Mahout (Hadoop)

MapReduce programming model, 2nd Marcus, Gary

marketing

massively parallel processing (MPP) databases, 2nd medical research (case study)

MetaMind

micro-conversions, 2nd Microsoft, 2nd

Microsoft Power BI Microsoft Research

minimum viable product (MVP), 2nd, 3rd MLlib (Spark)

model training model transparency models

deploying designing

fitting (training/calibrating), to data MongoDB, 2nd

Monte Carlo simulations, 2nd National Security Agency (NSA) Neo4j software, 2nd

Netflix, 2nd, 3rd, 4th, 5th

Netscape Communications Corporation

neural networks. see artificial neural networks

Nielsen

noSQL databases Nurego

online customer journey online publishing

open-source advantages of for big data history of, 2nd

open-source software, 2nd code distribution

licenses for

operational requirements OpEx, 2nd

organization, successful deployment in data-driven

data silos

focus on business value getting right people on board measuring results

reasons for, projects failure remembering to stay agile Otto group

outsourcing personal data

personally identifiable information (PII), 2nd personas, 2nd

petabytes (PB), 2nd

physical movement, records of Platform as a Service (PaaS), 2nd platform engineers

The Post

predictive analytics predictive maintenance Predix

premier image recognition challenge (case study) prescriptive analytics

pricing methods

principal component analysis privacy laws

private clouds, 2nd

Proceedings of the National Academy of Sciences

processing power, plummeting cost of product customization

programme team

programming languages public clouds, 2nd

Python (programming language), 2nd, 3rd, 4th, 5th Qlik

quasi-identifiers

R (programming language), 2nd, 3rd, 4th, 5th random access memory (RAM)

plummeting cost of RankBrain

Rapid-Miner (software), 2nd RASCI model

Realeyes

recommendation engines

recurrent neural networks (RNNs)

relational database management system (RDMS) reporting specialists

Research & Development (R&D)

REST (representational state transfer) services, 2nd retargeting

retention, customer

return on investment (ROI), 2nd, 3rd revenue, demand and

RFM (Recency, Frequency, Monetary) Safe Harbour Decision, EU

Safe Harbour Provisions Salesforce, 2nd, 3rd, 4th

SAS Enterprise Miner, 2nd, 3rd, 4th schema-less databases

Science (magazine) scientific research scrum framework

search engine databases Sedol, Lee

Selenium tool

self-publishing, content generation and self-service analytics

self-service capabilities, 2nd sentiment analysis

ShopperTrak SimilarWeb Siri (Apple), 2nd

Snowden, Edward, 2nd social media, 2nd software, choosing

Software as a Service (SaaS), 2nd, 3rd software framework

Solr (Apache), 2nd

Spark framework, 2nd, 3rd, 4th, 5th split testing. see A/B testing Splunk

SPSS (IBM), 2nd

Square Kilometre Array (SKA)

The Square Kilometre Array (SKA) astronomy (case study) stakeholders, 2nd

Stallman, Richard

standard query language (SQL) Stanley, Jeremy

storage

distributed data storage limitations

types of

strategic expertise streaming data

supply chain management Tableau

Target Corporation, 2nd team building

technical expertise technologies, choosing

for big data solution cloud solutions considerations in

capabilities matching business requirements extent of user base

freedom to customizing technology future vision

industry buzz

integration with existing technology open source vs. proprietary technologies risks involved with adopting technology

scalability

technology recommendations total cost of ownership

data pipelines

delivery to end users hardware, choosing software, choosing technology pioneers technology stack, 2nd

tensor processing unit (TPU) TensorFlow (software), 2nd, 3rd terabytes (TB)

Teradata Tesco, 2nd

‘the God particle’. see Higgs boson particle three Vs

training. see model training training data, 2nd

Twitter, 2nd Uber

University of Washington unstructured data

variety velocity

version control system (VCS)

Video Privacy Protection Act of 1988 Visual Networking Index™

visualization

for diagnostic analytics tools

Vizio volume Walkbase

The Washington Post

predicting news popularity at (case study) waterfall method, for project planning Watson (computer)

Watson–Anderson failure in 2016 (case study) Waze software

web analyst(s) wide column stores

XML format Yahoo

yottabyte

YouTube, 2nd, 3rd zettabytes

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