Data Lake Market Analysis And Trends By Segmentations, Top Key Players, Geographical Expansion, Future Development & Forecast -2024

May 21 15:42 2024
Data Lake Market Analysis And Trends By Segmentations, Top Key Players, Geographical Expansion, Future Development & Forecast -2024
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), (US), Snowflake (US), and Dremio (US).
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

MarketsandMarkets forecasts the global data lake market size to grow from USD 7.9 billion in 2019 to USD 20.1 billion by 2024, at a Compound Annual Growth Rate (CAGR) of 20.6% during the forecast period. The major growth factors of the data lake industry include the increasing need to extract in-depth insights from growing volumes of data to gain competitive advantage, and simplified access to organizational data from departmental silos, mainframe, and legacy systems.

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The large enterprises segment to hold a larger market size during the forecast period

By organization size, large enterprises and Small and Medium-Sized Enterprises (SMEs) are the 2 main segments where data lake solutions are used. Of these, the large enterprises segment is the larger user within the data lake market due to the large volumes of data being generated by enterprises and the increasing need for software/technology to store, manage, and analyze this data.

Typically, large enterprises have a huge corporate network and organize a large number of events. Data lake solutions enable these enterprises to gain cheap storage solutions along with fast and reliable access to processed data, which can help them organize data and generate useful insights. However, the SMEs segment is expected to grow at a higher CAGR during the forecast period as they are keen to adopt cloud-based data lake solutions due to their cost-effectiveness, scalability, and agility.

By vertical, the healthcare and life sciences segment to grow at the highest CAGR during the forecast period

The data lake market by vertical is segmented into 9 categories, namely, 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). Of these, the healthcare and life sciences segment is expected to grow at a rapid pace during the forecast period due to the existence of a large patient pool, especially in large-sized hospitals specializing in various streams of medicine. These organizations implement data lake solutions to understand and enhance the overall patient experience, and enable data-driven, actionable analytics. These solutions further offer healthcare and life sciences organizations with cost-effective and scalable architecture for the collection and processing of large volumes of disparate data types.

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Unique Features in the Data Lake Market

Organisations may store and handle enormous volumes of structured, semi-structured, and unstructured data without worrying about storage constraints thanks to data lakes’ horizontal scalability design. They support a wide range of datasets from different sources and provide flexibility with regard to data kinds and formats.

Data lakes adopt a schema-on-read strategy as opposed to traditional databases, which demand a predetermined schema (schema-on-write). Thus, information can be consumed in its unprocessed state, and when reading or querying the data, the schema is applied. This feature decreases the amount of upfront data modelling work and increases agility.

Organisations are able to acquire and analyse streaming data from IoT devices, social media, logs, and other sources thanks to the real-time data ingestion and processing capabilities of modern data lakes. For applications that need to make decisions and gain insights in real time, this functionality is essential.

Tools for machine learning and advanced analytics combine with data lakes with ease. They give data scientists and analysts a single platform to use for developing and refining machine learning models, conducting exploratory data analysis, and putting those models into use.

By utilising low-cost, scalable storage technologies like cloud-based object storage or the Hadoop Distributed File System (HDFS), data lakes provide affordable storage solutions. This enables long-term, cost-effective storage of massive amounts of data.

Major Highlights of the Data Lake Market

The growing amount of data produced by companies, the demand for sophisticated analytics, and the uptake of big data technologies are all driving the market for data lakes. Businesses are spending more and more money on data lake solutions in order to handle and profit from their data.

The market for data lakes is being driven by the increasing volume of data generated by businesses, the need for advanced analytics, and the adoption of big data technologies. Companies are investing an increasing amount of money on data lake solutions to manage and make money from their data.

Artificial intelligence (AI) and advanced analytics projects revolve around data lakes. They give businesses a single location to store a variety of data formats, allowing them to use AI and machine learning techniques to predict trends, extract insights, and automate decision-making processes.

The integration of data lakes and data warehouses through the development of the data lakehouse architecture is a significant trend. With the performance and administration capabilities of data warehouses combined with the flexibility of data lakes, this hybrid method serves workloads related to both analysis and transactions.

Real-time data intake and processing capabilities are increasingly supported by data lakes. This facilitates the real-time collection and analysis of streaming data from several sources, including social media and Internet of Things devices, by organisations, allowing for prompt and well-informed decision-making.

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Top Companies in the Data Lake Market

The major data lake market vendors include Microsoft (US), Teradata (US), Oracle (US), Atos (France), Cloudera (US), AWS (US), IBM (US), Temenos (Switzerland), Informatica (US), SAS Institute (US), Zaloni (US), Koverse (US), HPE (US), Cazena (US), Google (US), (US), Snowflake (US), Dremio (US), TCS (India) and Exacaster (Lithuania). These players have adopted various growth strategies, such as partnerships, agreements, and collaborations; and new product launches, to further expand their presence in the global data lake market. Partnerships, new product launches, and product enhancements have been the most dominating strategies adopted by major players from 2017 to 2019, which has helped them to innovate on their offerings and broaden their customer base.

Microsoft (US) develops and supports software, services, devices, and solutions. The company’s product offerings include Operating Systems (OS), cross-device productivity applications, server applications, business solution applications, desktop and server management tools, software development tools, and video games. The company designs, manufactures, and sells devices, such as Personal Computers (PCs), tablets, gaming and entertainment consoles, other intelligent devices, and related accessories. It offers a range of services, which include solution support, consulting services, and cloud-based solutions that provide customers with software, services, platforms, and content. In the data lake market, the company offers the Azure Data Lake solution, which comprises of offerings, such as Data Lake Analytics, Azure Data Lake Storage, and HDInsight. Azure Data Lake works with the existing Information Technology (IT) investments to identity, manage, and secure simplified data. It integrates easily with operational stores and data warehouses, enabling the use of current data applications. The solution solves productivity and scalability challenges that prevent users from maximizing the value of their data assets.

AWS (US) offers cloud computing services in the form of web services. The company offers a wide range of products and services to customers present across 190 countries. Its product portfolio comprises segments, such as compute, storage, database, migration, network and content delivery, developer tools, management tools, media services, Machine Learning (ML), and analytics. The solutions segment offers website and web apps, mobile services, backup, storage and archive, financial services, and digital media. AWS caters to verticals, such as media and entertainment, healthcare, government, education, and utilities. In the data lake market, the company offers Data Lake on AWS solution, which stores and registers datasets of any size in their native form in a secure, durable, and highly-scalable Amazon S3. Customers can upload datasets with searchable metadata and integrate with the AWS Glue and Amazon Athena to transform and analyze the uploaded data.

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