Ventana Research recently published the findings of ourbenchmark research on Data Preparation, which examines the practices organizations use to accomplish data preparation. We view data preparation as a sequence of steps: identifying, locating and then accessing the data; aggregating data from different sources; and enriching, transforming and cleaning it to create a single uniform data set. Using data to accomplish organizational goals requires that it be prepared for use; to do this job...
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Topics:
Big Data,
Analytics,
Data Preparation
I recently attended SAP TechEd in Las Vegas to hear the latest from the company regarding its analytics and business intelligence offerings as well as its data management platform. The company used the event to launchSAP Data Hub and made several other data and analytics announcements that I’ll cover below.
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Topics:
Big Data,
SAP,
Machine Learning,
Analytics,
Data Preparation
The Strata Data Conference is changing and it’s changing in a good way. At the recent Strata Data Conference in New York, Mike Olson, chief strategy officer at Cloudera, which co-sponsored the event, commented that at prior events we used to talk about the “Hadoop zoo animals,” meaning the various components of the Hadoop ecosystem of which I have written previously. Following last fall’s Strata event, I observed that the conference was evolving to focus on the use of data. Advancing that...
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Topics:
Big Data,
Machine Learning,
Analytics,
Hadoop,
Artificial intelligence,
Strata Data Conference
There’s been some speculation in the market that Hadoop may be disappearing. Some of this speculation has been driven by vendors that have recently downplayed Hadoop in their marketing efforts. For example, the Strata+Hadoop World conference is now known as the Strata Data Conference. The Hadoop Summit is now known as the Dataworks Summit. In Cloudera’s S-1 filing with the SEC for its initial public offering, the term “Hadoop” appears only 14 times, while the term “machine learning” appears 83...
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Topics:
Big Data,
Analytics,
Hadoop,
data lakes
Recently Hortonworksannounced some significant additions to its products at the DataWorks Summit. These additions reflect the fact that the big data market continues to evolve, as I have previouslywritten.
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Topics:
Big Data,
Machine Learning,
Analytics,
Hadoop
Natural language generation (NLG), the process of generating text or narratives based on a set of data values, can reach a broader audience. NLG narratives can be used for a variety of purposes, but in this perspective I focus on how NLG can be used to enhance business intelligence (BI) processes. In the case of BI, NLG can be used to explain what has happened and why it is happening, and even what actions to take. The NLG narratives can be understood by a broader range of business users than...
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Topics:
Machine Learning,
Natural Language,
Analytics,
Business Intelligence,
NLG
Many organizations continue to struggle with preparing data for use in operational and analytical processes. We see these issues reported in our Data and Analytics in the Cloud benchmark research, where 55 percent of organizations identify data preparation as the most time-consuming task in their analytical processes. Similarly, in our Next-Generation Predictive Analytics research, 62 percent of companies report that they’re unsatisfied because data needed for access or integration is not...
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Topics:
Big Data,
Analytics,
Collaboration,
Data Preparation,
Datawatch
This is my second analyst perspective based on ourIoT Benchmark Research. In thefirst, I discussed the business focus of IoT applications and some of the challenges organizations are facing. Now I’ll share some of the findings about technologies used in IoT applications and the impact those technologies appear to have on the success of users’ projects.
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Topics:
Big Data,
Analytics,
Business Intelligence,
IOT,
NoSQL
This year various types of organizations are embracing machine learning like it is going out of style – or maybe it would be better to say coming into style. And now with a little investigation on LinkedIn finds over half million professionals with machine learning in their job title. Machine learning is the application of specific data science algorithms that become more accurate as the system records more outcomes and processes more data. This improvement is referred to as “learning,” hence...
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Topics:
Big Data,
Data Science,
Analytics,
Business Intelligence,
Cloud Computing,
Machine Learning and Cognitive Computing,
Machine Learning Digital Technology
Informatica reintroduced itself to the world at its recent customer conference, Informatica World, in San Francisco. The company took advantage of the event to showcase its new branding in an effort to change the way customers think about the company. Informatica has been providing information services in the cloud for more than a decade. Even though cloud revenue comprises a minority of Informatica’s business, in absolute terms, the revenue is significant, and company executives want the...
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Topics:
Big Data,
Data Science,
Analytics,
Business Intelligence,
Cloud Computing,
Data Governance,
Data Integration,
Data Preparation,
Information Optimization,
Machine Learning and Cognitive Computing,
Machine Learning Digital Technology