Our research shows that nearly all financial service organizations (97%) consider it important to accelerate the flow of information and improve responsiveness. Even just a few years ago, capturing and evaluating this information quickly was much more challenging, but with the advent of streaming data technologies that capture and process large volumes of data in real time, financial service organizations can quickly turn events into valuable business outcomes in the form of new products and...
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Topics:
Analytics,
Internet of Things,
Data,
Digital Technology,
Streaming Analytics
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
The technology industry throws around a lot of similar terms with different meanings as well as entirely different terms with similar meanings. In this post, I don’t want to debate the meanings and origins of different terms; rather, I’d like to highlight a technology weapon that you should have in your data management arsenal. We currently refer to this technology as data virtualization. Other similar terms you may have heard include data fabric, data mesh and [data] federation. I’ll briefly...
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Topics:
Analytics,
Data Governance,
Data Integration,
Data,
Digital Technology,
data lakes
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
Data governance is a hot topic these days. In fact, we are conducting benchmark research on the subject here. With increasing regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), organizations face more external oversight of their data governance practices. The risk of significant fines associated with these and other regulations, coupled with organizations’ internal compliance requirements, has brought more attention to data...
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Topics:
Analytics,
Data Governance,
Data,
Digital Technology
Collibra is a data governance software company that offers tools for metadata management and data cataloging. The software enables organizations to find data quickly, identify its source and assure its integrity. Line-of-business workers can use it to create, review and update the organization's policies on different data assets. Collibra’s software uses a microservice architecture and open application programming interfaces to connect to various data ecosystems. Its data intelligence cloud...
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Topics:
business intelligence,
Analytics,
Data Governance,
Data Preparation,
Information Management,
Data,
data lakes,
AI and Machine Learning
Sisu Data is an analytics platform for structured data that uses machine learning and statistical analysis to automatically monitor changes in data sets and surface explanations. It can prioritize facts based on their impact and provide a detailed, interpretable context to refine and support conclusions. The product features fact boards, annotations and the ability to share facts and analysis across teams. Data teams and analysts start by creating common definitions of key performance...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data,
AI and Machine Learning
Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization. Rapidminer Studio is its visual workflow designer for the creation of predictive models. It offers more than 1,500 algorithms and functions in their library, along with templates, for...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data Preparation,
Data,
data lakes,
AI and Machine Learning
Confluent Platform is a streaming platform built by the original creators of Apache Kafka. It enables organizations to organize and manage streaming data from various sources. Confluent launched its IPO in June this year and raised $828 million to further expand its business. Confluent Platform was brought to several public cloud vendor marketplaces last year as Confluent Cloud. The offering is currently available in Azure, AWS, and GCP marketplaces. Furthermore, the company strengthened its...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Collaboration,
Data,
AI and Machine Learning