Dublin, Jan. 16, 2020 (GLOBE NEWSWIRE) -- The "Data Lake Market by Component, Deployment Mode, Organization Size, Business Function (Marketing, Operations, and Human Resources), Industry Vertical (BFSI, Healthcare and Life Sciences, Manufacturing), and Region - Global Forecast to 2024" report has been added to ResearchAndMarkets.com's offering.
The global data lake market size is projected to grow from USD 7.9 billion in 2019 to USD 20.1 billion by 2024, at a CAGR of 20.6% during the forecast period.
The major growth factors of the data lake market include the increasing need to extract in-depth insights from growing volumes of data to gain a competitive advantage, and simplified access to organizational data from departmental silos, mainframe, and legacy systems.
The report includes the study of the key players offering data lake solutions and services. It profiles major vendors in the global data lake market. The major vendors include Microsoft (US), Teradata (US), Oracle (US), Cloudera (US), AWS (US), IBM (US), Informatica (US), SAS Institute (US), Zaloni (US), Koverse (US), HPE (US), Cazena (US), Google (US), Infoworks.io (US), Snowflake (US), Dremio (US), and Talend (US). It further includes an in-depth competitive analysis of key players in the data lake market, along with their company profiles, business overviews, product offerings, recent developments, and market strategies.
Services segment to grow at a higher CAGR during the forecast period
Solutions and services are the 2 primary components available in the data lake market. The services segment, which covers managed and professional services, is expected to grow at a rapid pace during the forecast period. Increasing deployment of data lake software solutions leads to the increasing the demand for pre- and post-deployment services, as these solutions require training due to technical complexities, thus driving the growth of the segment.
Healthcare and life sciences vertical to grow at the highest CAGR during the forecast period
The data lake market by vertical has been segmented into Banking, Financial Services and Insurance (BFSI), telecommunication and Information Technology (IT), retail and eCommerce, healthcare and life sciences, manufacturing, energy and utilities, media and entertainment, government, and others (travel and hospitality, transportation and logistics, and education). The healthcare and life sciences segment is expected to grow at a rapid pace during the forecast period as healthcare organizations are adopting data lake solutions to enhance patient experience, and enable data-driven and actionable analytics.
APAC to grow at the highest CAGR during the forecast period
Asia Pacific (APAC) is expected to grow at the highest CAGR during the forecast period owing to increasing investments by technology companies in major APAC countries, such as China, Australia and New Zealand (ANZ), Japan, and India; growing digitalization; increasing adoption of advanced big data and analytics technologies; and government regulations and initiatives are expected to drive the growth of the market in the APAC region.
Research Coverage
The study covers the data lake market across segments. It aims at estimating the market size and the growth potential of this market, across different segments, such as component, deployment mode, organization size, business function, industry vertical, and region. The study further includes an in-depth competitive analysis of the key players in the market, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.
Key Topics Covered
1 Introduction
2 Research Methodology
3 Executive Summary
4 Premium Insights
4.1 Attractive Market Opportunities in the Data Lake Market
4.2 Market Top 3 Business Functions
4.3 Market By Region
4.4 Market in North America, By Business Function and Industry Vertical
5 Market Overview and Industry Trends
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Simplified Access to Organizational Data in Departmental Silos, Mainframe, and Legacy Systems
5.2.1.2 Increasing Need to Extract In-Depth Insights From Growing Volumes of Data to Gain Competitive Advantage
5.2.2 Restraints
5.2.2.1 Absence of Metadata in Data Lake Leading to Data Swamps
5.2.3 Opportunities
5.2.3.1 Shift Toward Cloud-Based Data Platforms to Manage and Mitigate Data Issues
5.2.3.2 Rise in Adoption of Advanced Technologies, Such as AI and Analytics
5.2.4 Challenges
5.2.4.1 Complexities Due to Regulatory Compliance for Data Usage
5.3 Use Cases
5.4 Regulatory Implications
5.4.1 General Data Protection Regulation
5.4.2 Payment Card Industry Data Security Standard
5.4.3 The International Organization for Standardization 27001
5.4.4 California Consumer Privacy Act
5.4.5 Health Insurance Portability and Accountability Act of 1996
5.4.6 Health Information Technology for Economic and Clinical Health Act
5.4.7 European Market Infrastructure Regulation
5.4.8 Basel Committee on Banking Supervision 239 Compliance
5.4.9 Sarbanes-Oxley Act of 2002
5.4.10 Personal Data Protection Act
5.5 Enterprise Data Lake Architecture
6 Data Lake Market By Component
6.1 Introduction
6.2 Solutions
6.3 Data Discovery
6.3.1 Growing Need to Identify the Useful Content in Data Driving the Adoption of Data Discovery Solutions
6.4 Data Integration and Management
6.4.1 Need to Ingest, Manage, and Govern Data Driving the Adoption of Data Integration and Management Solutions
6.5 Data Lake Analytics
6.5.1 Growing Demand for Real-Time Data Analytics to Make Business Decisions Driving the Adoption of Data Lake Analytics Solutions
6.6 Data Visualization
6.6.1 Business Need to Better Understand Insights Generated From Data Lake Analytics Driving the Adoption of Data Visualization Solutions
6.7 Services
6.7.1 Managed Services
6.7.1.1 Growing Need for Businesses to Focus on Core Operations and Streamline Automated Processes for Data Management Driving the Demand for Managed Services
6.7.2 Professional Services
6.7.2.1 Increase in Technicalities in the Deployment and Implementation of Data Lake Solutions to Drive the Demand for Professional Services
6.7.3 Consulting
6.7.3.1 Technicalities in Data Lake Solutions to Boost the Demand for Consulting Services
6.7.4 System Integration and Deployment
6.7.4.1 Need for Seamless Deployment of Data Lake Solutions to Drive the Demand for System Integration and Deployment Services
6.7.5 Support and Maintenance
6.7.5.1 Growing Deployment of Data Lake Solutions to Fuel the Demand for Support and Maintenance Services
7 Data Lake Market By Deployment Mode
7.1 Introduction
7.2 On-Premises
7.2.1 Need for Data Security to Boost the Adoption of On-Premises Data Lake Solutions
7.3 Cloud
7.3.1 Benefits Such as Cost-Effectiveness and Scalability to Drive the Adoption of Cloud-Based Data Lake Solutions
8 Data Lake Market By Organization Size
8.1 Introduction
8.2 Large Enterprises
8.2.1 Need to Store Large Volumes of Data Being Generated From Business and Customers and Enable Data-Driven Decisions Driving the Adoption of Data Lake Solutions and Services in Large Enterprises
8.3 Small and Medium-Sized Enterprises
8.3.1 Need to Store Data of the Growing Target Audience Globally and Extract Greater Value From Their Data Driving the Adoption of Data Lake Solutions in Small and Medium-Sized Enterprises
9 Data Lake Market By Business Function
9.1 Introduction
9.2 Marketing
9.2.1 Increased Demand for Precise Buyer Segmentation to Fuel the Adoption of Data Lake Solutions in Marketing
9.3 Sales
9.3.1 Need to Generate Automated Sales Pattern to Enhance Customer Targeting Driving the Adoption of Data Lake Solutions in Sales
9.4 Operations
9.4.1 Growing Need to Enhance Operations By Evaluating Internal Processes Driving the Adoption of Data Lake Solutions in Operations
9.5 Finance
9.5.1 Need to Manage Fraud and Risks By Determining Creditworthiness and Market Volatility Driving the Adoption of Data Lake Solutions in Finance
9.6 Human Resources
9.6.1 Need to Predict Leadership Needs and Perform Employee Sentiment Analysis Driving the Adoption of Data Lake Solutions in Human Resources
10 Data Lake Market By Industry Vertical
10.1 Introduction
10.2 Banking, Financial Services, and Insurance
10.2.1 Growing Need to Personalize Customer Engagement and Mitigate Risks Driving the Adoption of Data Lake Solutions in the Banking, Financial Services, and Insurance Industry Vertical
10.3 Telecommunications and It
10.3.1 Ability of Data Lake Solution to Visualize Complex Networks and Optimize Operations Driving Its Adoption in the Telecommunications and It Industry Vertical
10.4 Retail and Ecommerce
10.4.1 Growing Demand for Personalized Buyer Segmentation and Real-Time Customer Behavior-Based Experience Driving the Adoption of Data Lake Solutions in the Retail and Ecommerce Industry Vertical
10.5 Healthcare and Life Sciences
10.5.1 Growing Need to Leverage Data to Control Fraud, Enhance Patient Experience, and Offer Personalized Treatment in Real Time Driving the Adoption of Data Lake Solutions in the Healthcare and Life Sciences Industry Vertical
10.6 Manufacturing
10.6.1 Growing Need to Adapt to the Changing Needs of Businesses, Extend the Lifespan of Factory Equipment, Enhance Product Quality, and Reduce the Risk of Production Delays Driving the Adoption of Data Lake Solutions in the Manufacturing Industry Vertical
10.7 Energy and Utilities
10.7.1 Growing Need to Analyze the Data Being Generated From Smart Meters and Assets Driving the Adoption of Data Lake Solutions in the Energy and Utilities Industry Vertical
10.8 Media and Entertainment
10.8.1 Need to Manage and Utilize the Growing Data Flow From Social Media and Personalize Viewer Experience Driving the Adoption of Data Lake Solutions in the Media and Entertainment Industry Vertical
10.9 Government
10.9.1 Growing Demand for Enhanced Data Security and Advanced Intelligence to Boost the Adoption of Data Lake Solutions in the Government Sector
10.1 Others
11 Data Lake Market By Region
11.1 Introduction
11.2 North America
11.3 Europe
11.4 Asia-Pacific
11.5 Middle East & Africa
11.6 Latin America
12 Competitive Landscape
12.1 Overview
12.2 Competitive Leadership Mapping
12.2.1 Visionary Leaders
12.2.2 Innovators
12.2.3 Dynamic Differentiators
12.2.4 Emerging Companies
13 Company Profiles
13.1 Introduction
13.2 Microsoft
13.3 AWS
13.4 IBM
13.5 Oracle
13.6 Cloudera
13.7 SAS Institute
13.8 Informatica
13.9 Teradata
13.10 TCS
13.11 Atos
13.12 Google
13.13 HPE
13.14 Cazena
13.15 Zaloni
13.16 Temenos
13.17 Dremio
13.18 Exacaster
13.19 Koverse
13.20 Upsolver
13.21 Infoworks.IO
13.22 Snowflake
13.23 Bigstep
13.24 Right-To-Win
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