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        Analyst Perspectives

        Data is becoming more valuable and more important to organizations. At the same time, organizations have become more disciplined about the data on which they rely to ensure it is robust, accurate and governed properly. Without data integrity, organizations cannot trust the information produced by their data processes, and will be discouraged from using that data, resulting in inefficiencies and reduced effectiveness.

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        Topics: business intelligence, Analytics, Data Governance, Data Preparation, Information Management, Data, data lakes

        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: PROS Pricing, embedded analytics, Analytics, Business Intelligence, 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

        Teradata is not a name that is commonly associated with the customer experience marketplace, but that is likely to change as customer experience (CX) practitioners wrestle with the problems created by the multiple streams of data thrown off by the many applications and customer touchpoints they have to manage. Teradata’s Vantage CX is a tool for ingesting and managing customer information at great scale, combining the functions of a modern CDP with the analytics that makes customer data...

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        Topics: Customer Experience, Marketing, Analytics, Business Intelligence, Contact Center, Data, Digital Marketing, Digital Commerce, intelligent marketing, AI and Machine Learning

        Although historically there has been a hard divide between what are colloquially called “Inside and Field Sales,” changes over the last 10 years have narrowed the distinction. The pandemic has only accelerated the path to unifying sales activities commonly performed to engage buyers and customers. Characterized by a very disciplined and controlled endeavor, inside sales teams have been heavier users of technology. This has enabled more productive engagement including emails and calls, as well...

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        Topics: Sales, embedded analytics, Analytics, Business Intelligence, Collaboration, Internet of Things, Sales Performance Management (SPM), natural language processing, intelligent sales, sales enablement, AI and Machine Learning

        The annual Ventana Research Digital Innovation Awards showcases advances in the productivity and potential of business applications, as well as technology that contributes significantly to improved efficiency and productivity in the processes and the performance of an organization. Our goal is to recognize technology and vendors that have introduced noteworthy digital innovations that advance business and IT.

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        Topics: Analytics, Collaboration, Data Governance, Data Lake, Data Preparation, IOT, Data, Information Management (IM), Digital Technology, blockchain, Conversational Computing, collaborative computing, mobile computing, extended reality, AI and Machine Learning

        Determining and providing the appropriate compensation for each person — whether it involves base pay, variable pay such as commissions or bonuses or longer-term incentives in the form of cash or equity or other rewards — is critical to being able to attract and retain productive members of the workforce, whether full- or part-time employees, contingent workers or contractors. The complexities of compensation often prove to be a core challenge for human resources departments as they strive to...

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        Topics: Analytics, collaborative computing, total rewards management, AI and Machine Learning

        Every organization performing analytics with multiple employees needs to collaborate. They should be collaborating in the analytics process and in communicating the results of those analyses. As I continue my evaluation of analytics and data vendors, I have to admit some disappointment at the level of collaborative capabilities some analytics vendors provide. To be fair, the level of capabilities vary widely, but I expected collaborative capabilities to be more uniformly available as a standard...

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        Topics: business intelligence, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, Digital Technology, collaborative computing
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        Our Analyst Perspective Policy

        • Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business, industry and technology vendor trends. Each Analyst Perspective presents the view of the analyst who is an established subject matter expert on new developments, business and technology trends, findings from our research, or best practice insights.

          Each is prepared and reviewed in accordance with Ventana Research’s strict standards for accuracy and objectivity and reviewed to ensure it delivers reliable and actionable insights. It is reviewed and edited by research management and is approved by the Chief Research Officer; no individual or organization outside of Ventana Research reviews any Analyst Perspective before it is published. If you have any issue with an Analyst Perspective, please email them to ChiefResearchOfficer@ventanaresearch.com

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