Having just completed the 2021 Ventana Research Value Index for Analytics and Data, I want to share some of my observations about how the market has advanced since our assessment two years ago. The analytics software market is quite mature and products from any of the vendors we assess can be used to effectively deliver information to help your organization improve its operations. However, it’s also interesting to see how much the market continues to advance and how much investment vendors...
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Topics:
Big Data,
embedded analytics,
Analytics,
Business Collaboration,
Business Intelligence,
Collaboration,
natural language processing,
Conversational Computing,
collaborative computing,
mobile computing,
AI and Machine Learning
Organizations are increasingly using data as a strategic asset, which makes data services critical. Huge volumes of data need to be stored, managed, discovered and analyzed. Cloud computing and storage approaches provide enterprises with various capabilities to store and process their data in third-party data centers. The advent of data platforms previously discussed here are essential for organizations to effectively manage their data assets.
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data Governance,
Data Lake,
Data Preparation,
Data,
Microsoft Azure,
AI and Machine Learning
Ventana Research recently announced its 2021 market agenda for Analytics, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value from technology investments to improve business outcomes.
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
natural language processing,
Process Mining,
Streaming Analytics,
AI and Machine Learning
The industry is making huge strides with artificial intelligence (AI) and machine learning (ML). There is more data available to analyze. Analytics vendors have made it easier to build and deploy models, and AI/ML is being embedded into many types of applications. Organizations are realizing the value that AI/ML provides and there are now millions of professionals with AI or ML in their title or job description. AI/ML is even being used to make many aspects of itself easier. Organizations that...
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Topics:
Sales,
Customer Experience,
Marketing,
Analytics,
Business Intelligence,
Data Preparation,
Digital Technology,
AI and Machine Learning
Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs. A combination of complex data lake and data warehouse capabilities are required to leverage this data. Our research shows that nearly three-quarters of organizations deploy both data lakes and data warehouses but are using a variety of approaches which can be cumbersome. A single platform that can...
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Data,
data lakes,
AI and Machine Learning
Businesses are transforming their organizations, building a data culture and deploying sophisticated analytics more broadly than ever. However, the process of using data and analytics is not always easy. The necessary tools are often separate, but our research shows organizations prefer an integrated environment. In our Data Preparation Benchmark Research, we found that 41% of participants use Analytics and Business Intelligence tools for data preparation.
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data Preparation,
Information Management,
Internet of Things,
Data,
Digital Technology,
natural language processing,
Conversational Computing,
AI and Machine Learning
Traditional on-premises data processing solutions have led to a hugely complex and expensive set of data silos where IT spends more time managing the infrastructure than extracting value from the data. Big data architectures have attempted to solve the problem with large pools of cost-effective storage, but in doing so have often created on-premises management and administration challenges. These challenges of acquiring, installing and maintaining large clusters of computing resources gave rise...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data Governance,
Data Preparation,
Data,
data lakes,
AI and Machine Learning
Organizations are always looking to improve their ability to use data and AI to gain meaningful and actionable insights into their operations, services and customer needs. But unlocking value from data requires multiple analytics workloads, data science tools and machine learning algorithms to run against the same diverse data sets. Organizations still struggle with limited data visibility and insufficient insights, which are often caused by a multitude of reasons such as analytic workloads...
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Data,
Information Management (IM),
data lakes,
AI and Machine Learning
Ventana Research has been evaluating analytics and business intelligence (BI) software for a long time—almost 20 years. Our methodology for these assessments is referred to as a Value Index. We use weightings derived from our benchmark research about how you, as buyers of these technologies, value and evaluate vendors. You can view our 2019 Value Index results here. I am in the process of completing the 2020 evaluation now.
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Topics:
business intelligence,
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Data Preparation,
Information Management (IM),
natural language processing,
Conversational Computing,
collaborative computing,
software evaluation,
AI and Machine Learning
Artificial intelligence (AI) and machine learning (ML) are all the rage right now. Our Machine Learning Dynamic Insights research shows that organizations are using these techniques to achieve a competitive advantage and improve both customer experiences and their bottom line. One type of analysis an organization can perform using AI and ML is predictive analytics. Organizations also need to plan their operations to predict the amount of cash they will need, inventory levels and staffing...
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Topics:
Office of Finance,
Analytics,
Business Intelligence,
Financial Performance Management,
Digital Technology,
Predictive Planning,
AI and Machine Learning