Data Lake Market Forecast: Reaching US$ 19.8 Bn by 2030 with a CAGR of 24.8% | Cloudera, Tencent Cloud, Dell Technologies

Description

A data lake is a centralized repository that allows you to store all structured and unstructured data at any scale. It provides cost-effective storage for various data types like log files, images, videos, kafka streams etc. Large enterprises use data lakes for omnichannel analytics, data science and machine learning.

Coherent Market insights announces the release of the report "Data Lake Market - Demand, Growth, Opportunities and Analysis of Top Key Player Forecast to 2030", The Data Lake market research report provides a comprehensive analysis of the current state and future potential of the Data Lake market. The report covers various aspects, including market size, growth trends, key players, market segmentation, competitive landscape, industry drivers, and challenges. The objective of this report is to assist stakeholders, investors, and businesses in making informed decisions and formulating effective strategies to thrive in the Data Lake market, are provided. In addition, the report provides key insights about market drivers, restraints, opportunities, new product launches or approvals, COVID-19 and Russia-Ukraine War Influence.

According to Coherent Market Insights study, The Data Lake Market size is expected to reach US$ 19.8 Billion by 2030, from US$ 4.2 Billion in 2023, at a CAGR of 24.8% during the forecast period.

The Data Lake market is a diverse industry that encompasses multiple sectors, including (mention specific sectors, e.g., technology, healthcare, finance, etc.). Over the past few years, the market has experienced significant growth due to technological advancements, changing consumer preferences, and increasing demand for innovative services.

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The major players operating in the market include:

➱ Amazon Web Services
➱ Microsoft
➱ IBM
➱ Oracle
➱ Cloudera
➱ Informatica
➱ Teradata
➱ Zaloni
➱ Snowflake
➱ Dremio
➱ HPE
➱ SAS Institute
➱ Google
➱ Alibaba Cloud
➱ Tencent Cloud
➱ Baidu
➱ VMware
➱ SAP
➱ Dell Technologies
➱ Huawei

These companies are focusing on new product development, partnerships, collaborations, and mergers and acquisitions to increase their market share and maintain their position in the market.

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Market Dynamics:

The data lake market is expected to witness significant growth owing to growing need for centralization of enormous amounts of data across various industries and the need to obtain valuable insights from this data. Moreover, increasing digitization across sectors is generating huge volumes of data requiring cost-effective storage and analytics. Additionally, rising adoption of cloud-based data lakes and growing demand for unified views of information are further propelling the market growth over the forecast period. Emergence of technologies like artificial intelligence, internet of things and machine learning is augmenting large scale data generation, thus driving the need for scalable data lakes.

Major Drivers for Data Lake Market Growth

Increasing adoption of big data analytics technologies

The volume of data being generated is growing exponentially with the proliferation of IoT devices and digitalization of business processes. This massive amount of data holds opportunities for businesses to gain valuable insights and make informed decisions. However, extracting meaningful insights from big data requires powerful analytics technologies. Data lake provides a scalable data store and analytics platform to gain insights from both structured and unstructured data. Organizations across industries are leveraging data lake to unlock value from their data assets through advanced analytics techniques like machine learning and artificial intelligence.

Need for centralized data management and governance

Modern businesses deal with data residing across disparate databases, file systems and cloud storage. Aggregating and managing these distributed silos of data is a challenging task. A data lake addresses this challenge by providing a single repository to consolidate all types of data from multiple sources. It enables consistent management, metadata tagging and access control of centrally stored data. This centralized model streamlines regulatory compliance, security and privacy of sensitive information. Central data governance ensures quality, standardization and readiness of data for strategic decision making.

Major Restrain for Data Lake Market Growth

Complexity in data integration and preparation

Bringing together heterogeneous data from diverse operational systems into a unified data lake requires intensive data integration and preparation efforts. Raw data usually needs to be processed, cleansed, transformed and structured before analytics. This involves resolving issues like incompatible data formats, missing attributes and duplicates - a task that demands significant time and technical expertise. The complexity and cost of data wrangling acts as a deterrent for organizations, especially those with limited resources and skills.

Key Opportunity for Data Lake Market Growth

Leveraging data lake for AI/ML model training

Data lake is emerging as a preferred platform for artificial intelligence and machine learning initiatives. Its scale and flexibility enable researchers and data scientists to easily access large volumes of raw training data. Advanced deep learning models consume huge amounts of unlabeled and unlabeled examples for self-learning. A data lake centralized repository supports iterative model building by providing on-demand access to vast datasets. Its schema-on-read approach also simplifies feature engineering - a critical step in ML workflows. This makes data lake an attractive option for enterprises focusing on AI/ML driven product innovation and customer experiences.

Notable Trend in the Data Lake Market

Growth of cloud-based data lake offerings

Cloud computing providers like AWS, Microsoft Azure and Google Cloud are increasingly pushing managed cloud data lake services. These services allow migrating on-premise data lakes to the cloud and deliver elastic scalability of storage and compute resources on pay-as-you-go pricing. Companies can avoid upfront capital expenditures and do away with infrastructure maintenance overheads. Major cloud players are also introducing AI/ML based features to accelerate data preparation, auto classification and predictive analytics on data lakes. Such advancements are set to reinforce cloud adoption for data lakes and drive the next phase of market expansion.

Data Lake Market Segmentation:

By Component

Solutions
◘ Data Discovery
◘ Data Integration and Management
◘ Data Lake Analytics
◘ Data Visualization
◘ Others
Services
◘ Managed Services
◘ Professional Services

By Deployment Mode
◘ On-premises
◘ Cloud

By Organization Size
◘ SMEs
◘ Large Enterprises

By Business Function
◘ Marketing
◘ Operations
◘ Finance
◘ Human Resources

By Industry Vertical
◘ BFSI
◘ Healthcare and Life Sciences
◘ Manufacturing
◘ Retail & E-commerce
◘ Government & Defense

Market segment by Region/Country including:

- North America (United States, Canada and Mexico)
- Europe (Germany, UK, France, Italy, Russia and Spain etc.)
- Asia-Pacific (China, Japan, Korea, India, Australia and Southeast Asia etc.)
- South America (Brazil, Argentina and Colombia etc.)
- Middle East & Africa (South Africa, UAE and Saudi Arabia etc.)

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Frequently Asked Questions (FAQs):

➱ What are the key factors hampering growth of the Data Lake market?
➱ What are the major factors driving the global Data Lake market growth?
➱ Which is the leading component segment in the Data Lake market?
➱ Which are the major players operating in the Data Lake market?
➱ Which region will lead the Data Lake market?
➱ What will be the CAGR of Data Lake market?
➱ What are the drivers of the Data Lake market?

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This release was published on openPR.