Advanced Analytics Market

[286 Pages Report] The advanced analytics market is projected to grow from USD 64.3 billion in 2023 to USD 226.2 billion by 2028, at a compound annual growth rate (CAGR) of 28.6% during the forecast period. The advanced analytics market is expected to grow significantly during the forecast period, owing to various business drivers.. Advanced Analytics solutions and services facilitates organizations make data-driven decisions, uncover hidden patterns, identify opportunities, and mitigate risks. The market is experiencing significant growth as more businesses embrace data-driven decision-making. Moreover, the rising adoption of big data and related technologies creates a fertile environment for advanced analytics solutions to thrive.

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Advanced Analytics Market Dynamics

Driver: Rising adoption of big data and other related technologies to stimulate market growth and leverage real-time data processing

The use of advanced technologies, such as cloud, IoT, big data and analytics, mobility, and social media, has led to innovation and transformation, thereby stimulating growth in the business ecosystem. Digital technologies have transformed the legacy approach to business into a modern approach. For example, online services are now firmly established in the banking and financial sector, resulting in the proliferation of online activities and websites. According to a blog by Usabilla (Netherlands) in June 2020, the top 100 organizations are 50% more likely to address customer empowerment as a key parameter for business growth. The blog also stated that 92% of leaders had employed advanced digital transformation strategies to enhance customer experience. Moreover, big data technologies enable organizations to capture, store, and process large volumes of structured and unstructured data from diverse sources. This abundance of data provides a rich foundation for advanced analytics solutions to extract valuable insights and patterns. Big data technologies enable the processing of data in real time or near real time. This allows organizations to analyze streaming data and make immediate data-driven decisions. Advanced analytics solutions can leverage this real-time data processing to provide timely insights for proactive actions. The rising adoption of big data and related technologies creates a fertile environment for advanced analytics solutions to thrive. These technologies enable organizations to harness the power of data, extract meaningful insights, and drive data-driven decision-making, thereby fueling the increased adoption of advanced analytics in the market.

Restraints: Concerns related to data privacy and security

One of the major concerns for users of advanced analytics is data privacy. The backbone of advanced analytics solutions, data, remains a critically important aspect that most organizations find difficult to manage. The inefficiency of managing exabytes and petabytes of data has increased the chances of security breaches and data losses. In today’s competitive marketplace, marketing teams require real-time and secure data to deliver an outstanding customer experience. Organizations are gathering data through multiple touchpoints and measuring them virtually. Such data is used in support and communication and may include various data types. These data types comprise public information, big data, and small data collected from customers. This data can include permissions, individual preferences, and updated contact information on products, services, and communication platforms. Hence, vendors need to ensure high-level data security to maintain customer trust. Recently, cybercriminals have gained access to widespread tools to obtain anything from passwords to secret questions and token-generated passwords. In such situations, marketing and IT teams must work concurrently, providing each other with insights on when and how the data is gathered, processed, and used in operations. Such potent cyberattacks continue to hinder the widespread adoption of advanced analytics across data-intensive industrial sectors. However, this scenario is expected to gradually change throughout the forecast period as the benefits of technology adoption continue to outweigh the risks associated with overall developments on the data security front.

Opportunity: Advancements in AI and ML technologies for improved algorithms and extract more actionable insights

Advancements in AI and machine learning algorithms continue to enhance the capabilities of advanced analytics solutions. Improved algorithms, automated model building, and deep learning techniques enable organizations to extract more accurate and actionable insights from data, driving the adoption of advanced analytics. AI and ML algorithms continue to advance, enabling more accurate predictions and insights from data. Advanced analytics solutions can leverage these algorithms to analyze large volumes of data, identify patterns, make predictions, and uncover valuable insights that can drive strategic decision-making. AI and ML advancements facilitate automated model building and optimization processes. This reduces the need for manual model development and tuning, saving time and resources for organizations. Advanced analytics solutions can leverage automated model building techniques to streamline the analytics process and enable faster deployment of models. Moreover, AI and ML advancements empower advanced analytics solutions to deliver personalized experiences and recommendations. By analyzing user behavior, preferences, and historical data, organizations can provide tailored recommendations, product suggestions, and personalized marketing campaigns, driving customer engagement and satisfaction.

Challenge: Complex data ecosystem leading to data breaches and security issues

Data consolidation helps transform the gathered data into a single format, thus simplifying the decision-making process for companies. Data exchanges and data ecosystems deliver the tools to analyze the collected data at a centralized location and help extract and cross-check business-critical components. The development of data exchanges and data ecosystems varies based on the assumptions made on the value of the data for each customer segment. However, since centralized data is more prone to cyberattacks, data exchanges are a major concern for data-sensitive organizations in industry verticals such as Banking, Financial Services, and Insurance (BFSI) and healthcare, which deal with individual data. Such organizations need to take extreme care to ensure the safety of customers’ personal information. Data breaches impact an organization’s identity and security; fool-proof security measures are a priority. In some countries, the concerned organizations are partially responsible for the damage triggered by the loss of confidential data. Enterprises must also ensure the security of data outsourced to a third-party BI vendor for analysis. However, with companies increasingly adopting data security solutions, consumer data security is not expected to be a major long-term issue.

Advanced Analytics Market Ecosystem

By offering, solutions segment to account for larger market size during forecast period

The advanced analytics solutions utilize various statistical, mathematical, and machine learning techniques to discover patterns, correlations, and trends in data. Organizations decide to deploy on-premises or cloud-based advanced analytics solutions based on the size of their organization, security concerns, pricing and budget, and customization needs. The cloud segment is estimated to lead the advanced analytics market in 2028 due to security and data privacy concerns.

By business function, operations & supply chain to register highest CAGR during forecast period

The operations & supply chain segment is projected to grow more during the forecast period. Advanced analytics in operations enables companies to strike the right balance between operational cost, speed, flexibility, and quality. Many companies today are facing challenges in conducting operational management analysis. Today, almost every organization has started deploying analytics technologies, such as IoT, ERP systems, cloud computing, and social media for operation management.

By region, North America to have largest market size during forecast period

North America is expected to lead the advanced analytics market in 2023. The US is the largest market for advanced analytics in North America. The North American market for advanced analytics is being driven by several factors, including  the increasing adoption of advanced technologies, presence of supporting infrastructure, and drive for early technological adoption, due to the competition from other businesses operating in the other regions.

In addition,  North America has a strong ecosystem of startups and venture capitalists focused on AI, which is helping to drive innovation in the field. Many of the leading companies in the advanced analytics market are based in North America, including IBM, Oracle, Microsoft and SAS Institute.

Key Market Players

The advanced analytics solution and service providers have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgradations, partnerships, and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. Some major players in the advanced analytics market include IBM (US), Oracle (US), Google (US), SAP (Germany), Microsoft (US), SAS Institute (US), KNIME (Switzerland), FICO (US), Altair (US), AWS (US), Salesforce (US), TIBCO Software (US), Alteryx (US), Teradata (US), Adobe (US), Absolutdata Analytics (US), Moody’s Analytics (US), Qlik (US), Databricks (US), Dataiku (US), Kinetica (US), MathWorks (US), Anaconda (US), H2O.ai (US), Domino Data Lab (US), DataRobot (US), DataChat (US), Imply (US), Promethium (US), Siren (Ireland), Tellius (US), SOTA Solutions (Germany), and Vanti Analytics (Israel).

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Scope of the Report

This research report categorizes the advanced analytics market based on offering, type, business function, vertical, and region.

By Offering:

• Solutions
• Services

By Type:

• Big Data Analytics
• Predictive Analytics
• Customer Analytics
• Statistical Analytics
• Risk Analytics
• Prescriptive Analytics
• Other Type

By Business Function:

• HR
• Sales & Marketing
• Finance & Accounting
• Operations & Supply Chain
• Other Business Functions

By Vertical:

• BFSI
• IT and ITES
• Retail & Consumer Goods
• Manufacturing
• Automotive & Transportation
• Healthcare & Life Sciences
• Media & Entertainment
• Government & Defense
• Telecom
• Other Verticals

By Region:

• North America
  • US
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Rest of Europe
• Asia Pacific
  • China
  • India
  • Japan
  • Australia and New Zealand (ANZ)
  • South Korea
  • ASEAN Countries
  • Rest of Asia Pacific
• Middle East & Africa
  • UAE
  • Saudi Arabia
  • South Africa
  • Israel
  • Rest of the Middle East & Africa
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America

Recent Developments:

• In June 2023, IBM Cognos Analytics accelerates data-driven decisions with AI-powered insights for everyone in the organization. The latest version extends its analytics capabilities in a single, secure environment integrated with IBM’s data fabric architecture.
• In May 2023, SAP and IBM announced that IBM Watson technology will be embedded into SAP solutions to provide new AI-driven insights and automation.
• In May 2023, SAP and Google Cloud announced an extensive expansion of their partnership, introducing a comprehensive open data offering designed to simplify data landscapes and unleash the power of business data.
• In March 2023, Oracle has extended its collaboration with NVIDIA to include running strategic NVIDIA AI applications on the new Oracle Cloud Infrastructure (OCI) Supercluster.
• In March 2023, Google Cloud and Exabeam announced a partnership to help organizations detect and respond to security threats faster and more accurately.

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