With the release of the Dell EMC™ Analytic Insights Module, enterprises now have a platform that can address the full analytics lifecycle. Analytic Insights Module is engineered to combine self-service data analytics with cloud-native application development into a single cloud platform, eliminating the months it takes to build your own.
Hadoop is fast becoming the center piece of a modern data architecture. And Cloudera Enterprise provides the centralized management and robust support that you need to effectively operate Hadoop.
The modern data architecture stores data as is; it doesn't require pre-modeling. It needs to accommodate volume, velocity, and variety including structured and unstructured information. Hadoop does this very well.
Many of our customers use Hadoop. And Attivio's full-platform certification on Cloudera Enterprise will help them streamline their modern data architecture by offering agile data access wherever data resides.
As Dan Woods points out in a recent article for Forbes, technology marketplaces cycle through predictable stages as they mature. He applies this insight to the component versus platform decision that organizations face when adopting new technologies.
As any developer knows, perfect software doesn’t just happen it, pardon the pun, “develops” over time. Developers engage in a seemingly everlasting iterative process involving bug fixes and changes that can last for the lifetime of an application. But writing the software is only half the battle; it must then be deployed.
For big data companies like ours that run software across distributed networks, this is no small task. In particular, a developer makes changes, runs tests, identifies errors or processing improvements to address, and then makes more changes.
I recently attended Hadoop Summit 2016 where not surprisingly there was a lot of conversation about topics other than Hadoop. For example, the importance of ecosystem partners to any Big Data solution.
It was a great conversation. Carey pointed out that although data scientists do spend a lot of time on analytics, they also spend just as much or more time "wrangling" their data environments and trying to find data and move it where they need it. And that's why EMC turned to Attivio and Zaloni. Check out the rest of the discussion.
Attivio is excited to be a part of EMC’s new Big Data Solution. It’s not generally available yet, so we thought we’d have a chat with Ted Bardasz from EMC to give you a look at what this new platform offering is and how Attivio fits in.
Q: Tell me about your role at EMC.
TB: I am the Senior Director of Product Management in the Converged Platform Division, responsible for our Big Data and Native Hybrid Cloud solutions.
You understand that data is the lifeblood of innovation and competitive differentiation. The key is to get the right data into the hands of business analysts when they need it. Sounds simple in theory, but challenges abound. However, for every challenge enterprises face surfacing and connecting the right data, there is an answer.
Let me explain:
From Process Bottlenecks to Busting Bottlenecks
For any data gathering process to work well, business and IT must be aligned. When they aren’t on the same page, when there needs to be a continual back and forth discussion about what data is needed, there is a bottleneck. IT doesn’t know what the data means, business analysts and data stewards don’t necessarily know what data is there.
The answer to this question is straightforward within the context of quantitative disciplines like mathematics in which “linear” and “non-linear” are well defined and differentiated. The answer is less obvious in reference to data management and analysis. The industry acknowledges that a traditional, strictly linear IT-centric approach is ineffective in view of today’s evolving data landscape. Many organizations advocate bypassing IT altogether with non-linear solutions emphasizing self-service data discovery, preparation and analysis in order to accelerate the transition from raw data to insights.
There's a lot of talk these days about how to streamline the data supply chain. And the discussions often boil down to how to control an organization's data and how difficult and time consuming it is for business users to access it. As I wrote recently for DataInformed, highly structured systems for managing data like master data management (MDM) and enterprise data warehouses (EDWs) put a kink in the data supply chain. They aspire to a single version of the truth but at a cost in time-to-insight few enterprises can afford to pay.