다양한 산업에서 생성되는 데이터 양 증가, 고급 분석의 필요성, 기업이 다양한 데이터 형식에서 의미있는 정보를 추출할 수 있게 해주는 저렴한 데이터 관리 솔루션에 대한 수요가 데이터 레이크 시장을 추진하는 주요 요인입니다. Verified Market Research의 분석가에 따르면 데이터 레이크 시장은 2024년 약 172억 1,000만 달러의 평가 금액 미만으로 예측 기간 동안 790억 9,000만 달러의 평가 금액에 도달할 것으로 예상됩니다.
헬스케어 업계는 전자건강기록(EHR), 의료영상, 유전체 시퀀싱에 의해 생성되는 대량의 환자 데이터를 관리 및 분석할 필요가 있기 때문에 데이터 레이크 시장의 성장에 크게 기여할 것으로 예상됩니다. 이에 따라 이 시장은 2024년부터 2031년까지 약 21.00%의 연평균 복합 성장률(CAGR)로 성장할 전망입니다.
데이터 레이크 시장 정의 및 개요
데이터 레이크는 많은 소스로부터 구조화, 반구조화, 비구조화 데이터를 포함한 대량의 원시 데이터를 사전 정리하지 않고 자연스러운 형식으로 저장할 수 있는 중앙 집중식 저장소입니다. 이러한 유연성을 통해 기업은 비즈니스 앱, IoT 기기, 소셜 미디어 등 다양한 소스에서 데이터를 검색하고 유지할 수 있으며, 필요에 따라 고급 분석 및 머신러닝을 수행할 수 있습니다. 데이터 레이크는 빅데이터 분석, 실시간 데이터 처리, 예측 모델링 등 다양한 용도로 활용되고 있으며, 방대한 데이터세트에서 통찰력을 얻어 의사결정 프로세스를 개선하고자 하는 기업에 필수적인 존재가 되고 있습니다.
업계 전반에 걸쳐 데이터 생산량이 크게 증가함에 따라 데이터 레이크 수요가 늘어나고 있습니다. International Data Corporation(IDC)에 의하면, 세계의 데이터 스피어는 2018년의 33 제타바이트에서 2025년에는 175 제타바이트로 증가할 것으로 예상되고 있습니다. 이 데이터 양의 431%라는 경이적인 증가에는 이 폭발적인 데이터를 관리하고 거기서 가치를 끌어내기 위한 데이터 레이크와 같은 확장 가능하고 유연한 스토리지 솔루션이 필요합니다.
빅데이터 분석과 인공지능 및 머신러닝(AI/ML) 기술의 이용 증가가 데이터 레이크 시장을 견인하고 있습니다. 뉴 밴티지 파트너스 조사에 따르면 저명 기업의 91.9%가 2021년까지 빅데이터와 AI 투자를 확대할 예정입니다. 데이터 레이크는 고급 분석과 AI/ML 애플리케이션에 필요한 방대한 양의 이종 데이터를 저장하고 처리하는 데 필요한 인프라를 제공합니다.
게다가 클라우드 컴퓨팅으로의 전환은 클라우드 기반 데이터 레이크의 보급을 가속화하고 있습니다. 가트너는 2021년 30%에서 2025년까지 새로운 디지털 워크로드의 95% 이상이 클라우드 네이티브 플랫폼에 구현될 것으로 예측하고 있습니다. 이 동향은 확장성, 비용 효율성, 분산 데이터 처리와 분석을 지원하는 능력을 이유로 기업이 클라우드 기반 데이터 레이크를 이용하도록 장려하고 있습니다.
데이터 거버넌스의 복잡성은 데이터 레이크 시장의 성장을 막는 큰 장벽이 되고 있습니다. 조직이 다양한 소스에서 대량의 원시 데이터를 수집함에 따라 데이터의 품질, 보안, 컴플라이언스 확보가 더욱 복잡해지고 있습니다. 강력한 거버넌스 프레임워크가 없으면 기업은 데이터 무결성과 규제 컴플라이언스에 과제가 발생하고 부정확한 분석과 불충분한 의사결정으로 이어질 위험이 있습니다. 이러한 복잡성은 거버넌스 프로세스와 테크놀로지에 막대한 투자를 필요로 하기 때문에 데이터 레이크 이용을 단념하는 기업도 있습니다.
게다가 데이터 레이크 내에서의 데이터 품질 유지의 어려움도 중요한 제약이 되고 있습니다. 데이터는 클렌징이나 밸리데이션을 거치지 않고 그대로 흡수되는 경우가 많기 때문에 오류나 부정확성이 발생할 수 있습니다. 이러한 품질 관리의 결여는 하류의 분석이나 의사 결정 프로세스에 바람직하지 않은 영향을 미쳐 잘못된 인사이트를 가져옵니다. 이러한 위험을 방지하기 위해 조직은 강력한 데이터 품질 기준을 채택해야 합니다
The growing amount of data produced by various industries, the need for sophisticated analytics, and the demand for affordable data management solutions that let businesses extract meaningful information from various data formats are the main factors propelling the data lake market. According to the analyst from Verified Market Research, the data lakes market is estimated to reach a valuation of USD 79.09 Billion over the forecast subjugating around USD 17.21 Billion valued in 2024.
The healthcare industry is expected to contribute substantially to the growth of the data lake market, owing to the requirement to manage and analyze massive amounts of patient data generated by electronic health records (EHRs), medical imaging, and genomic sequencing. It enables the market to grow at a CAGR of about 21.00% from 2024 to 2031.
Data Lakes Market: Definition/ Overview
A data lake is a centralized repository that can store large amounts of raw data in its natural format, including structured, semi-structured, and unstructured data from many sources without the need for prior organizing. This flexibility enables businesses to consume and maintain data from a variety of sources, including business apps, IoT devices, and social media, allowing them to execute advanced analytics and machine learning as needed. Data lakes are used in a variety of applications, including big data analytics, real-time data processing, and predictive modeling, making them critical for companies looking to get insights from massive datasets and improve decision-making processes.
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The substantial rise in the production of data across industries has fueled the demand for data lakes. According to the International Data Corporation (IDC), the global datasphere is expected to increase from 33 zettabytes in 2018 to 175 zettabytes by 2025. This staggering 431% rise in data volume needs scalable and flexible storage solutions such as data lakes to manage and extract value from this data explosion.
The increased use of big data analytics and artificial intelligence/machine learning (AI/ML) technologies is driving the data lake market. According to NewVantage Partners' survey, 91.9% of prominent organizations plan to increase their investments in big data and AI initiatives by 2021. Data lakes provide the necessary infrastructure to store and handle enormous volumes of heterogeneous data needed for advanced analytics and AI/ML applications.
Furthermore, the shift to cloud computing is accelerating the popularity of cloud-based data lakes. Gartner anticipates that by 2025, more than 95% of new digital workloads will be implemented on cloud-native platforms, up from 30% in 2021. This trend is encouraging enterprises to use cloud-based data lakes because of their scalability, cost-effectiveness, and capacity to support distributed data processing and analytics.
The complexity of data governance is a major barrier to growth in the data lakes market. As organizations collect massive amounts of raw data from a variety of sources, ensuring data quality, security, and compliance becomes more complex. Without a strong governance framework, firms risk experiencing challenges with data integrity and regulatory compliance, resulting in incorrect analytics and poor decision-making. This complexity needs significant investment in governance processes and technologies, discouraging some companies from using data lakes.
Furthermore, the difficulty of maintaining data quality within data lakes is another important constraint. Because data is frequently absorbed in its raw form without previous cleansing or validation, errors and inaccuracies may occur. This absence of quality control has an unfavorable effect on downstream analytics and decision-making processes, resulting in incorrect insights. To prevent these risks, organizations must employ strong data quality standards that involve significant resources and expertise.
The solution segment is estimated to dominate the data lakes market during the forecast period. Organizations are increasingly looking for advanced analytics skills to extract useful insights from large amounts of data. The solutions segment, which includes data discovery, integration, and analytics tools, allows businesses to easily process and analyze raw data. The demand for sophisticated analytical tools is accelerating the expansion of the solutions segment significantly.
The requirement for efficient data integration and management solutions grows as organizations amass heterogeneous datasets from several sources. The solutions segment meets this need by offering tools that assist enterprises in streamlining data ingestion, storage, and processing. This capability not only improves operational efficiency but also allows for superior decision-making processes, boosting the solutions segment's market dominance.
Furthermore, data lakes provide exceptional scalability and flexibility, enabling businesses to store and manage massive amounts of organized and unstructured data. The solutions segment capitalizes on this advantage by offering scalable infrastructures that can adapt to an organization's changing data requirements. This adaptability is particularly appealing to businesses trying to future-proof their data initiatives, reinforcing the solutions segment's market leadership.
The banking, financial services, & insurance (BFSI) segment is estimated to dominate the market during the forecast period. The BFSI industry relies extensively on data for decision-making processes such as risk assessment, fraud detection, and consumer insights. Data lakes enable financial institutions to store massive amounts of structured and unstructured data, allowing for advanced analytics and machine learning applications that boost operational efficiency and service delivery.
The BFSI industry is subject to severe regulations governing data management and reporting. Data lakes provide a consolidated repository that makes compliance easier by allowing firms to keep detailed records of transactions and consumer interactions. This feature promotes good data governance and enables financial institutions to respond quickly to regulatory audits and inquiries.
Furthermore, in an increasingly competitive landscape, BFSI firms are focused on individualized customer experiences to retain customers and attract new ones. Data lakes enable these firms to gather and analyze a variety of customer data sources, allowing them to personalize products, services, and marketing campaigns to individual tastes. This focused strategy improves consumer satisfaction and loyalty, hence driving segment growth.
North America is estimated to dominate the data lakes market during the forecast period. North America leads in technological adoption and digital transformation activities, which fuels the demand for data lakes. According to IDC, US businesses are estimated to invest USD 1.8 Trillion in digital transformation activities by 2025. This large investment demonstrates the region's commitment to using advanced data management technologies, such as data lakes, to support digital objectives and preserve a competitive advantage.
Furthermore, the rapid proliferation of Internet of Things (IoT) devices in North America is generating large volumes of data, increasing the demand for data lakes. IoT Analytics predicts that North America will have 5.4 billion IoT connections by 2025, indicating a 14% compound annual growth rate (CAGR). This boom of connected devices generates massive volumes of heterogeneous data, necessitating scalable storage and processing solutions, establishing data lakes as a critical component of the region's IoT ecosystem.
The Asia Pacific region is estimated to exhibit the highest growth within the market during the forecast period. The Asia Pacific region is experiencing a spike in mobile and internet adoption, resulting in massive amounts of data that must be efficiently stored and analyzed. According to GSMA Intelligence, the Asia Pacific region's mobile internet user base will grow from 2.7 billion in 2021 to 3.1 billion by 2025. This rapid increase in connected people generates massive amounts of heterogeneous data, making data lakes critical for organizations to acquire, store, and derive insights from this wealth of information.
Furthermore, many Asian countries are implementing national initiatives to encourage big data and artificial intelligence, resulting in increased demand for data lakes. China's New Generation Artificial Intelligence Development Plan intends to make the country a world leader in AI by 2030, with an estimated core AI industry gross output of over 1 trillion yuan (~ USD 150 Billion). Similarly, India's National Strategy for Artificial Intelligence predicts that AI will bring $957 billion to the Indian economy by 2035. These government-supported initiatives are hastening the adoption of data lakes as the basic infrastructure for big data and AI projects throughout the region.
The competitive landscape of the data lakes market is fragmented, with multiple competitors fighting for market share in various regions and sectors. Organizations in a variety of industries, including retail, healthcare, and manufacturing, are increasingly using data lake solutions to leverage massive amounts of structured and unstructured data for better decision-making and operational efficiencies.
Some of the prominent players operating in the data lakes market include:
Microsoft
IBM
Oracle
Cloudera
Informatica
Teradata
Zaloni
Snowflake
Dremio
HPE
SAS Institute
Alibaba Cloud
Tencent Cloud
Baidu
VMware
SAP
Dell Technologies
Huawei
In December 2022, Atos announced the development of a new solution in collaboration with AWS that allows clients to expedite and properly monitor company key performance indicators (KPIs) by offering simple access to non-SAP and SAP data silos. 'Atos' AWS Data Lake Accelerator for SAP" is an innovative solution that delivers enterprise-wide and self-service reporting for significant insights into daily changes that rapidly impact decisions to drive the bottom line.
In November 2022, Amazon Web Services (AWS) announced the launch of Amazon Security Lake. This new cybersecurity solution automatically centralizes safety data from on-premises and cloud sources into a purpose-built data lake in a user's AWS account.
In April 2022, Google introduced the preview launch of Big Lake. This new data lake storage system allows organizations to analyze data in their data lakes and warehouses at its Cloud Data Summit.