ISG Software Research Analyst Perspectives

Organizations today have an ever-increasing appetite for platforms that improve the speed and efficiency of data analytics and business intelligence (BI). The ability to quickly process data enables organizations to make well-informed decisions in real time. This agile approach to data processing is crucial for staying ahead in today's competitive landscape. With the rising need for data-driven insights, organizations face the difficulty of dealing with massive volumes of distributed business data and the limitations of traditional data warehousing approaches. Given these challenges, organizations are seeking new and advanced data platforms to efficiently derive real-time business insights. And analytic data platform vendors are responding accordingly. We assert that through 2024, analytic data platform vendors will continue to accelerate the delivery of actionable insight by integrating native data integration, data management, analytics and machine learning (ML) with their core data persistence and processing functionality. Incorta is a prime example, with its open data delivery platform designed to enable organizations to accelerate the delivery of business insights from big data sets. Incorta was founded in 2013 to streamline and accelerate the data analytics process with its data delivery platform. It does this by consolidating functionality for data acquisition, data management and data analysis into a single analytic data platform. The platform can connect with databases and big data platforms, cloud applications, ERP systems, and other business applications through its intuitive user interface, and it can store and process data using the company’s in-memory, columnar analytics engine. Analysts can utilize Incorta's own data exploration and presentation tools, while Incorta also offers the flexibility to utilize any SQL-compliant front-end tools, such as Microsoft Power BI or Tableau. Other vendors are also consolidating functionality for data acquisition, data management and data analysis, but Incorta remains differentiated by its underlying Direct Data Mapping engine. This is designed to pre-process the data as it is loaded to determine potential query paths and accelerate query performance, enabling organizations to perform real-time operational analytics on data from business applications, without the need for upfront data modelling, transformation and optimization. Personnel can join multiple data sources and use the platform to drill down to transaction-level details for enhanced data exploration. By eliminating the need for data reshaping or transformations, Incorta's Direct Data Mapping allows for rapid queries on normalized data models. Our Analytics and Data Benchmark Research shows that organizations have various concerns about analytics and BI. Most of them cite challenges such as finding it hard to integrate with their business processes, lack of flexibility or adaptability to change, and difficulties in accessing their data sources. Organizations can use Incorta to unify data processing to accelerate analytics and BI by reducing/eliminating the need for ETL processing prior to analysis. I wrote about Incorta last year, and since then, Incorta has further facilitated self-service analytics for business users via the introduction of data applications targeted at key use cases in finance, human resources, supply chain, manufacturing and sales and marketing. Incorta’s Data Applications are its prebuilt solutions that are designed to accelerate cloud migration and expedite the development of analytics, reporting, and AI functionalities. These data applications encapsulate best practices from the Incorta user community and provide users with prebuilt analytics, dashboard templates and content, enabling access, organization and presentation of data from popular business solutions, including such vendors as Oracle SAP, Workday and Salesforce. Last year, Incorta announced several updates and additions to its Analytics Data Hub for Finance offering, which is designed to provide a self-service platform for real-time analysis of financial and operational data. Among the notable enhancements, Incorta integrated BlackLine and Workday as new data destinations within Analytics Data Hub for Finance. These integrations enable IT teams to provide users real-time access to operational data, journal entries and subledger details, empowering accounting and FP&A teams to conduct detailed analysis of transactional data. Incorta also recently announced the acquisition of Cream Analytics, a software company focused on automating data collection and cleansing and the generation of key metrics and reports, as well as external context and industry benchmarks, for finance teams. The company has also expanded its support for data science and ML workloads and recently announced a collaboration with Google Cloud to simplify the delivery of data from complex business applications to Google Cloud, accelerating advanced analytics for supply chain, financial, sales, and marketing operations. The collaboration also provides a foundation for Incorta customers to take advantage of generative AI, thanks to native integration between Google Cloud Cortex Framework and Google Cloud’s generative AI technology. Incorta also previously collaborated with Google Cloud to facilitate real-time business analytics on ERP data in the cloud. Incorta should enhance its offerings by expanding supported data sources and providing more connectors for streamlined data integration. Additionally, incorporating advanced analytics capabilities like predictive modeling and native support for generative AI applications would boost the platform's value proposition. By offering a unified data platform with real-time operational analytics capabilities, Incorta addresses the increasing demand for agile data processing to support informed decision-making. We recommend that organizations seeking to enhance their data analytics and BI capabilities as well as accelerate data integration and processing should consider Incorta. Its integration capabilities and real-time analytics enable organizations to perform faster data analysis. Regards, Matt Aslett

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