RIM
Textual ETL is a groundbreaking solution that automates the transformation of large volumes of unstructured textual data into a relational database, preventing your data lake from becoming polluted with meaningless data.
FOREST RIM®’s Textual ETL reads, integrates, and prepares unstructured data ready to go into standard
technologies such as Oracle, DB2, Teradata, and NT SQL Server. Once the unstructured data resides in any of
those technologies, common analytical tools such as
Power BI, Qlik Sense, ThoughtSpot, Tableau, and other analytical and BI visualization technologies can be used to access, analyze, and present your unstructured data.
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Discover real-world applications of Textual ETL and how the technology can unlock the value hidden in unstructured textual data.
Helping Organizations, Governments, and Industries to better use and create value through unstructured textual data.
To be the world leader in converting textual unstructured data to a structured database so that organizations can gain deeper insights and make better decisions.
Helping Organizations, Governments, and Industries to better use and create value through unstructured textual data.
To be the world leader in converting textual unstructured data to a structured database so that organizations can gain deeper insights and make better decisions.
We drive and embrace new ways of doing things, and we are protagonists in the innovative use of data to transform how the world understands human communications.
We act with integrity and openness, and we bring our authentic selves to work. We foster an environment of trust, and we reinforce that trust through our actions.
We welcome ideas from everyone and admire the value in ourselves and others. We create real connections as colleagues and relationships based on mutuality and honesty.
We drive and embrace new ways of doing things, and we are protagonists in the innovative use of data to transform how the world understands human communications.
We act with integrity and openness, and we bring our authentic selves to work. We foster an environment of trust, and we reinforce that trust through our actions.
We welcome ideas from everyone and admire the value in ourselves and others. We create real connections as colleagues and relationships based on mutuality and honesty.
Best known as the “Father of Data Warehousing” Bill Inmon is the most prolific and well-known author worldwide in big data analysis, data warehousing, and business intelligence.
Our people are our strongest asset
Best known as the “Father of Data Warehousing”, Bill Inmon has become the most prolific and well-known author worldwide in the Big Data analysis, Data Warehousing and Business Intelligence arena. In addition to authoring more than 60 books and 1,000s of articles, Bill has been a monthly columnist with the Business Intelligence Network, EIM Institute and Data Management Review. In 2007, Bill was named by Computerworld as one of the “Ten IT People Who Mattered in the Last 40 Years” of the computer profession. He has worked for American Management Systems and Coopers & Lybrand. Bill received his Bachelor of Science degree in Mathematics from Yale University and his Master of Science degree in Computer Science from New Mexico State University. He makes his home in Colorado.
Originally from Richmond, Virginia Easley Edmunds has resided in Santiago, Chile since 2005. His affinity for Latin culture evolved during his academic career after multiple exchange programs. He has a dual degree in Finance & Spanish from James Madison University, and an MBA from the University Adolfo Ibáñez. His career in software started in 2008, when he was tasked with launching operations in Latin America for a well known publicly traded Fintech company, Intralinks. He built up the region from scratch, delivering double digit growth YoY for over a decade and positioning them as the market leader before transitioning to the data analytics space.
Mary possesses extensive experience in the development and execution of strategies to govern and master data in different industries across technology and business teams around the world. Prior to joining Forest Rim Technology, Mary was the founder of a consulting company to help organizations bring value through data. Mary is the Co-Author of the book ‘Data Architecture V2: A Primer for the Data Scientist’. She has Bachelor of Science and Master of Science degree in Engineering from Montana State University. Her passion is to help solve problems through data to improve the quality of people’s lives.
Tanler was founder of Information Advantage, Inc. a leader in the Business Intelligence/data warehousing market; author of The Intranet Data Warehouse; and recognized as Entrepreneur of the Year by Ersnt &Young after taking Information Advantage to an IPO. As Chief Innovation Officer of Forest Rim technology, Tanler is a Knowledge Graph Prophet. Semantic graph visualizations identify patterns in attitudes, opinions,desires; expressed in words that predict behavior. “Forest Rim is the second branch of Data Science, the analysis of communications that often precede actions”.
Discover real-world applications of Textual ETL and how the technology can unlock the value hidden in unstructured textual data.
Sentiment analysis in the call center: Hear the Voice of the Customer. Nearly every corporation has a call center. Ask an executive if his/her organization has a call center and the odds are good that the executive will say yes. Then you ask the executive whether or not he/she knows what is going on in the call center. The executive
The Original Data Challenge With the proliferation of applications came the problem of data integrity. The problem with the advent of large numbers of applications was that the same data appeared in many places with different values. In order to make a decision, the user had to find WHICH version of the data was the right one to use among
Big Data started out as a replacement for data warehouse. The Big Data vendors are loathe to mention this fact today. But if you were around in the early days of Big Data, one of the central topics that was discussed was – if you have Big Data do you need a data warehouse? From a marketing standpoint Big Data
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