Skip to main content

Data Management Analytics Spend will Reach $19.8B

More CIOs and CTOs are seeking actionable insight from the new technologies that are driving digital transformation within the industrial and manufacturing sectors. Manufacturing plants generate mountains of data throughout the day, every day. That data is a valuable asset.

Traditionally, data has been noted on paper or analyzed in spreadsheets. However, today it can be collected automatically via sensors and analyzed with tools that far exceed spreadsheet capabilities.

According to the latest worldwide market study by ABI Research, manufacturers and industrial companies will be spending $19.8 billion on data management, data analytics, and associated professional services by 2026.

Data Management and Analytics Market Development

"For many manufacturers, there is an appreciation that operational decisions need to be based on empirical evidence rather than guesswork. The challenges are not necessarily capturing and analyzing data, rather what to analyze in the first place," said Michael Larner, principal analyst at ABI Research.

According to the ABI assessment, the findings need to have a meaningful impact on operations and so manufacturers need to take a step back and devise precise objectives for data analytics projects.

Manufacturers should engage suppliers to help them prioritize activities and shape projects. For example, is the priority to increase production, reduce waste, improve quality, or to fully understand whether a piece of machinery needs to be serviced?

Predictive maintenance of manufacturing systems is critical for avoiding production downtime and improved employee safety on the factory floor. At the same time, video inspection software typically captures defects with a greater degree of accuracy than the human eye.

As the use cases expand, the IT supplier ecosystem evolves to meet them. For example, Bright Wolf, InVMA, and Dploy Solutions marry technological and consulting expertise to help their respective clients achieve digital transformation from a business perspective.

Davra looks to ensure manufacturers are using clean data, Relimetrics focuses on video inspections, Altair on analytics capabilities to support digital twins, and Senseye on predictive maintenance.

Moreover, the advancements in Artificial Intelligence (AI) and machine learning mean that IT suppliers can no longer merely report on captured data, they must also predict outcomes and suggest recommended actions for their customers.

Outlook for Data Analytics Use Case Growth

The orientation for action makes for compelling value propositions, and when combined with data visualization platforms embed data in many different roles. The advent of no-code and low-code platforms don't require IT staff to be data scientists to utilize software analytics in their roles.

"While manufacturers have spent decades refining their physical production lines, today they need to expend effort in optimizing their processes for collecting and analyzing data. But data should not be collected just for the sake of it," Larner concludes.

Clearly, there is a growing need for data analytics professional services within the industrial and manufacturing sectors. Business and IT leaders would greatly benefit from information and guidance that would enable operation teams to discover and apply the lessons learned by similar organizations.

Popular posts from this blog

Demand for Quantum Computing as a Service

The enterprise demand for quantum computing is still in its early stages, growing slowly. As the technology becomes more usable, we may see demand evolve beyond scientific applications. The global quantum computing market is forecast to grow from $1.1 billion in 2022 to $7.6 billion in 2027, according to the latest worldwide market study by International Data Corporation (IDC). That's a five-year compound annual growth rate (CAGR) of 48.1 percent. The forecast includes base Quantum Computing as a Service, as well as enabling and adjacent Quantum Computing as a Service. However, this updated forecast is considerably lower than IDC's previous quantum computing forecast, which was published in 2021, due to lower demand globally. Quantum Computing Market Development In the interim, customer spend for quantum computing has been negatively impacted by several factors, including: slower than expected advances in quantum hardware development, which have delayed potential return on inve

AI Semiconductor Revenue will Reach $119.4B

The Chief Information Officer (CIO) and/or the Chief Technology Officer (CTO) will guide Generative AI initiatives within the large enterprise C-Suite. They may already have the technical expertise and experience to understand the capabilities and limitations of Gen AI. They also have the authority and budget to make the necessary investments in infrastructure and talent to support Gen AI initiatives. Enterprise AI infrastructure is proven to be expensive to build, operate and maintain. That's why public cloud service provider solutions are often used for new AI use cases. AI Semiconductor Market Development Semiconductors designed to execute Artificial Intelligence (AI) workloads will represent a $53.4 billion revenue opportunity for the global semiconductor industry in 2023, an increase of 20.9 percent from 2022, according to the latest worldwide market study by Gartner. "The developments in generative AI and the increasing use of a wide range AI-based applications in data c

Industrial Cloud Computing Apps Gain Momentum

In the manufacturing industry, cloud computing can help leaders improve their production efficiency by providing them with real-time data about their operations. This has gained the attention of the C-suite. Total forecast Industrial Cloud platform revenue in manufacturing will surpass $300 billion by 2033 with a CAGR of 22.57 percent, driven by solution providers enhancing platform interoperability while expanding partner ecosystems for application development. ABI Research found the cloud computing manufacturing market will grow over the next decade due to the adoption of new architectural frameworks that enhance data extraction and interoperability for manufacturers looking to maximize utility from their data. Industrial Cloud Computing Market Development "Historically, manufacturers have built out their infrastructure to include expensive data housing in the form of on-premises servers. The large initial upfront cost of purchasing, setting up, and maintaining these servers is