Artificial Intelligence and Big Data Survey 2017, Volume 1

  • ID: 4342851
  • Report
  • 197 Pages
  • Evans Data Corp
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In March 2017, Facebook Introduced its New AI Hardware, Big Basin and Open Sourced the Design Specifications through the Open Computer Project

This series focuses on tools, methodologies, and concerns related to implementing machine learning, deep learning, image recognition, pattern recognition and other forms of artificial intelligence as well as efficiently storing, handling, and analyzing large datasets and databases from a wide range of sources.

Artificial intelligence is permeating software development in many ways and many industries, which necessitates a thorough knowledge of how developers are doing this. Big Data, often related, is also becoming a reality for more and more companies; this report provides valuable insight into developer opinions on these topics.

This volume includes research and analysis covering topics such as Implications of AI, AI & Big Data Developer Demographics, Decision-Making for AI & Big Data, Barriers and Challenges for Data Analytics, AI Concept and Approaches, Conversational Systems & Virtual Assistants, Optimizing Hardware for AI, Real-Time Events & Streams Processing, Big Data & IoT, Collaboration in Big Data & Data Science, Advanced Analytics Tools and Services, Databases & Data Warehousing, Hadoop, Parallelism & Big Data, and Tools Used for Data Analytics and Ingestion.

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EXECUTIVE SUMMARY
Objectives of the Survey
Survey Methodology
Research Design
Relative Rankings 
The Sample – Software Developers 
The EDC Panel
Other Evans Data Corpervices
Multi-Client Survey Series
Tactical Survey Reports
Custom Surveys
Targeted Analytics

DEMOGRAPHICS 
Developer Segment 
Job Role 
Involvement in Software Development 
Involvement in Decision Making
Industry
Company Size 
Company's Length of Time in Business
Team Size 
Team Composition for Big Data and Analytics Projects
Departments Using Artificial Intelligence Solutions
Development Prior to Working with AI

THE IMPLICATIONS OF ARTIFICIAL INTELLIGENCE 
How Do Projects Benefit from AI Integration?
Stage of Development Lifecycle where AI is Integrated
Job Categories Replaced by AI
Job Categories Supplemented by AI
Type of Project Supported by AI

DECISION-MAKING FOR ARTIFICIAL INTELLIGENCE AND BIG DATA
Plans for Using Artificial Intelligence and Machine Learning in Development
Involvement in Big Data and Advanced Analytics Projects
Industry Addressed by Big Data and Analytics Solutions
Who Chooses Security Solution for Big Data? 
Information Sources for Learning About Big Data and Machine Learning
Most Compelling Information When Evaluating Tools for Purchase 
Most Credible Information Sources for Big Data and Machine Learning 
Who Analyzes or Develops Big Data Projects 
Biggest Benefits of Big Data Implementation 
Most Exciting Trends for Big Data 

BARRIERS AND CHALLENGES FOR DATA ANALYTICS
Biggest Challenges with Data and Analytics
Top Concern when Moving from Proof of Concept to Production
Acceptable Downtime to Upgrade or Test Big Data Solutions 
Most Important Areas for Vendor Action to Help Secure Big Data

ARTIFICIAL INTELLIGENCE CONCEPTS AND APPROACHES
Familiarity with Artificial Intelligence and Machine Learning Concepts 
Level of Engagement with Deep Learning Methodologies 
Industries Targeted for Artificial Intelligence
Industries Targeted for Neural Networks 
Industries Targeted for Machine Learning
Industries Targeted for Deep Learning
Industries Targeted for Pattern Recognition
Industries Targeted for Natural Language Processing
Industries Targeted for Data Mining
Industries Targeted for Real Time Events Processing 
Industries Targeted for Big Data Analytics
Types of Processing and Analytics Integrated into Machine Learning App
Tools Used for Machine Learning
Implementations for Deep Learning Project
Types of Data Processed in Projects
Use of Image Recognition
Image Recognition Domains for AI Projects

CONVERSATIONAL SYSTEMS AND VIRTUAL ASSISTANTS
Speech Recognition in Applications 
Development of Conversational Systems or Virtual Assistants
Target Audience for Conversational Systems or Virtual Assistants
Use of Text Classification Algorithms for Conversational Systems or Virtual Assistants 
Approach to Developing Text Classification Algorithms 
Use Case for Conversational Systems or Virtual Assistants 
Spoken Languages Supported by Conversational Systems or Virtual
Assistants 
Industries Targeted by Conversational Systems or Virtual Assistants

OPTIMIZING HARDWARE FOR ARTIFICIAL INTELLIGENCE
Use of Tools or Techniques to Optimize AI Projects for Hardware
Architectures
Hardware Architecture Types Targeted with AI Optimizations
Hardware Architecture Types Primarily Targeted with AI Optimizations
Project Type Primarily Targeted with AI Optimized for Hardware

REAL-TIME EVENTS AND STREAMS PROCESSING
Importance of Real Time Complex Event Processing vsatch Processing
Expected Change in Real Time Event-based App Use
Complex Event Processing Methods
Languages Used for Stream Processing 
Runtimes Used for Stream Processing
Use of Open Source In-Stream Event Processing Software 

BIG DATA AND THE INTERNET OF THINGS
Primary Reason for Using Big Data with IoT Projects 
Supported Client Devices for Big Data
Plans for Supporting Client Devices for Big Data
Connected Device Interaction with Big Data
Connected Device Interaction by Client Device
Data Collected by Connected Devices 
Data Collected by Client Device
Connected Device Production
Concerns with the Internet of Things
Types of Connected Devices Targeted 
Challenges for Building IoT Apps
Projects Intersecting with Internet of Things Projects
Primary Focus of IoT Projects 
Types of Services or Platforms Used with IoT Projects
Importance of Various Support Features of IoT Tools and Platforms

BIG DATA AND THE CLOUD 
Cloud Focus for Big Data Solutions
Top Factors in Big Data Solution Selection
Top Three Reasons for Using Cloud to Deploy Big Data Apps
Preferred Approach to Organizing Private Clouds
Cloud-based API Types Preferred for AI or Big Data
Cloud Vendors Used to Host Analytics Applications
Cloud Vendors Used to Host Big Data
Cloud Vendors Used to Host AI Applications 

PARALLELISM AND BIG DATA
Use of Parallelism
Use of Parallelism by Company Size 
Use of Parallelism by Developer Segment
Issues with Parallel Programming 
Best Resources to Help Implement Parallelism
Best Parallelism Resources by Parallelism Use
Best Parallelism Resources by Developer Segment
Task or Data Parallelism 

DATABASES AND DATA WAREHOUSING
Top Three Factors for Choosing Database Technology 
Most Important Types of Data to Analyze for Data Security 
SQL Databases Integrated with Big Data Sets 
Percent of Data Stored As Non-Relational Data
Percent of App Data Stored in Relational Data Structures 
Types of In-Memory Databases in Use 
Fault Tolerance Processes Used 
Expected Growth of Data Stores 
Tools and Services Used for Data Ingest
Where Are Big Data Applications Implemented?
Percent of Data Stored On Site vsff site
Expected Change in Storage Distribution

USING HADOOP
Plans for Using Hadoop
Reason for Not Using Hadoop
Hadoop: On-Premises or the Cloud
Plans for Apache Spark
Distributed File System Used with Spark
Plans for YARN in Hadoop 
Plans for Using Hadoop Clusters 
Number of Nodes in Hadoop Cluster 
Required Memory for Hadoop Nodes
Underlying Operating System Used with Hadoop
Plans for Hadoop on OpenStack
Current Status of OLAP Usage with Hadoop 

ADVANCED ANALYTICS TOOLS AND SERVICES 
Data Feeds for Predictive Analytics
Number of Data Sources Used in Modeling
Size of Data Sets
Plans for Using Analysis Tools for Particular Tasks
Most Requested Improvement to Data and Analytics Tools
Most Requested Improvement by Company Size 
Primary Analytics Tools Being Used
Primary Analytics Tools Used for Predictive Models 
Maximum Latency for Analysis
Process of Record for Data Modeling

TOOLS FOR DATA ANALYTICS AND INGESTION
Most Important Considerations When Choosing Tools for Big Data or AI
Type of Data Processed in Project 
How is Incoming Data Processed by Software 
Text Input Formats Processed 
Input Documents Used
Is Incorrect Grammar an Issue?
Average Data Ingestion Rates 
Data Cleaning Tools Used
Data Mining Tools Used
Data Analysis Tools Used
Data Visualization Tools Used
Data Integration Tools Used 

COLLABORATION 
Frequency of Collaboration with Other Teams in a Big Data Project 
Collaboration with Business Units or Clients?
Changing Dynamics in Collaborating with Business Units and Clients 
Use of Collaboration Tools 
Collaboration Tools Used in Big Data Projects 
Collaboration with Data Scientists

OPERATING SYSTEMS AND LANGUAGES 
Languages Used with Big Data
Other Tools Used with Big Data
Languages Used with Artificial Intelligence
Other Tools Used with Artificial Intelligence
Importance of Hardware to Big Data or Machine Learning Projects 
Hardware Performance vsardware Efficiency 
Primary Host Operating System 
Primary Host Operating System by Company Size
Primary Operating System for Big Data Deployments 
Primary Operating System for Deployment by Developer Segment

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