Organizations of all sizes are dealing with exponentially increasing data volume and data sources, which creates challenges such as siloed information, increased technical complexities across various systems and slow reporting of important business metrics. Migrating to the cloud does not solve the problems associated with performing analytics and business intelligence on data stored in disparate systems. Also, the computing power needed to process large volumes of data consists of clusters of...
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Topics:
Analytics,
Business Intelligence,
Data Integration,
Data,
data lakes,
data operations,
Streaming Analytics,
AI and Machine Learning
I’m proud to share Ventana Research’s 2022 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operations during any type of disruption.
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Topics:
Analytics,
Cloud Computing,
Internet of Things,
Data,
Digital Technology,
AI and Machine Learning
Organizations today have huge volumes of data across various cloud and on-premises systems which keep growing by the second. To derive value from this data, organizations must query the data regularly and share insights with relevant teams and departments. Automating this process using natural language processing (NLP) and artificial intelligence and machine learning (AI/ML) enables line-of-business personnel to query the data faster, generate reports themselves without depending on IT, and...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Data Integration,
Data,
natural language processing,
data lakes,
data operations,
Data Platforms,
AI and Machine Learning
Organizations today are working with multiple applications and systems, including enterprise resource planning (ERP), customer relationship management (CRM), supply chain management (SCM) and other systems, where data can easily become fragmented and siloed. And as the organization increases its data sources and adds more systems and custom applications, it becomes challenging to manage the data consistently and keep data definitions up to date. This increases the need to use master data...
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Topics:
Analytics,
Business Intelligence,
Data Governance,
Data Integration,
Data,
Digital Technology,
Analytics & Data,
AI and Machine Learning
TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes. It offers more than 200 connectors, more than 200 enterprise cloud computing and application adapters, and more than 30 non-relational structured query language databases, relational database management...
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Topics:
embedded analytics,
Analytics,
Collaboration,
Data Governance,
Information Management,
Data,
Digital Technology,
data lakes,
AI and Machine Learning
Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. The platform enables personnel to work with relational databases, Apache Hadoop, Spark and NoSQL databases for cloud or on-premises jobs. Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a...
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Topics:
Analytics,
Business Intelligence,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Data,
Digital Technology,
data lakes,
AI and Machine Learning
How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad. Too often, the reader is expected to understand the difference, but...
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Topics:
business intelligence,
Analytics,
Internet of Things,
Data,
Digital Technology,
Streaming Analytics,
AI and Machine Learning
Databricks is a data engineering and analytics cloud platform built on top of Apache Spark that processes and transforms huge volumes of data and offers data exploration capabilities through machine learning models. It can enable data engineers, data scientists, analysts and other workers to process big data and unify analytics through a single interface. The platform supports streaming data, SQL queries, graph processing and machine learning. It also offers a collaborative user interface —...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data Governance,
Data Preparation,
Information Management,
Data,
data lakes,
AI and Machine Learning
Access to external data can provide a competitive advantage. Our research shows that more than three-quarters (77%) of participants consider external data to be an important part of their machine learning (ML) efforts. The most important external data source identified is social media, followed by demographic data from data brokers. Organizations also identified government data, market data, environmental data and location data as important external data sources. External data is not just part...
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Topics:
Analytics,
Business Intelligence,
Internet of Things,
Data,
Digital Technology,
Streaming Data,
Streaming Analytics,
AI and Machine Learning
Alteryx is a data analytics software company that offers data preparation and analytics tools to simplify and automate data wrangling, data cleaning and modeling processes, enabling line-of-business personnel to quickly access, manipulate, analyze and output data. The platform features tools to run a variety of analytic functions such as diagnostic, predictive, prescriptive and geospatial analytics in a unified platform, and can connect to various data warehouses, cloud applications,...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data Preparation,
Data,
AI and Machine Learning