Joyce Norris-Montanari explains why it's so important to pick the right tools to manage your big data.
David Loshin says simple approaches to identity resolution may not scale on a big data platform as data volumes increase.
Phil Simon chimes in on the last five years of Hadoop with an eye toward the future.
Joyce Norris-Montanari poses the question: Is Hadoop/big data technology actually ready for MDM?
Welche Rolle Datenqualität und Data Governance beim Data Management für Analytics spielen, habe ich mit meinem Kollegen Gerhard Svolba zuletzt an dieser Stelle diskutiert. Doch was genau macht modernes Datenmanagement aus, und welche Rolle spielen dabei neue Technologien à la Hadoop und Co.? Und wie sieht überhaupt die künftige Zusammenarbeit
Big Data Innovation Lab is an environment where you can bring all the people and technology together and test the analytical value of your data. The Lab comes with the latest data technologies to tackle data regardless of format, structure or size. You'll be able to experiment, make adjustments and if you find analytical
There aren’t many things that keep me awake at night but let me share a recent example with you. I’ve been grappling with how to help a local SAS team respond to a customer’s request for a “generic enterprise analytics architecture.” As background, this customer organization had recently embarked on
The digital revolution requires an ever-increasing number of repetitive and targeted decisions. The digital revolution is faster and more comprehensive than the Industrial Revolution at the beginning of the last century. It requires less capital, and focuses on intellectual and digital innovation, which is affordable to many. The innovations produced
We've all seen it before – a truck on the side of the road with the hood up and the driver desperate to figure out what’s wrong. In this situation, not only is a customer not receiving goods on time, but the problem is exacerbated by the fact that most
4 dominant trends can be distinguished in the development of Business Intelligence tools and in the way they are used in modern organisations. These trends will evolve into directions of development for these tools, changing their role in supporting decision processes and building competitive advantages. Trend 1: Self-service models The
As I discussed in the first two blogs of this series, metadata is useful in a variety of ways. Its importance starts at the source system, and continues through the data movement and transformation processes and into operations. Operational metadata, in particular, gives us information about the execution and completion
In the first blog of this four-part series, we discussed traditional data management and how we can apply these principles to our big data platforms. We also discussed how metadata can help bridge the gap of understanding the data as we move to newer technologies. Part 2 will focus on
Traditional data management includes all the disciplines required to manage data resources. More specifically, data management usually includes: Architectures that encompass data, process and infrastructure. Policies and governance surrounding data privacy, data quality and data usage. Procedures that manage a data life cycle from creation of the data to sunset
Nearly every organization has to deal with big data, and that often means dealing with big data problems. For some organizations, especially government agencies, addressing these problems provides more than a competitive advantage, it helps them ensure public confidence in their work or meet standards mandated by law. In this
It's that time of year again where almost 50 million Americans travel home for Thanksgiving. We'll share a smorgasbord of turkey, stuffing and vegetables and discuss fun political topics, all to celebrate the ironic friendship between colonists and Native Americans. Being part Italian, my family augments the 20-pound turkey with pasta –
Die aktuelle BARC-Studie verrät die Sicht der Unternehmen auf modernes Datenmanagement mittels Hadoop und Data-Lake-Konzepten. Die Anwenderbefragung gibt einen interessanten Blick auf den derzeitigen Status von Hadoop und Data Lakes in Europa und Nordamerika. Wo wird das Ecosystem eingesetzt, was ist der erhoffte Nutzen, und wo sind die Grenzen, um
Dies ist der zweite Teil der Blog-Serie zu Big Data Governance. Beginnen Sie vorher am besten mit „Teil 1: Wie Big Data Unternehmen durcheinanderwirbelt”, wenn sie ihn noch nicht gelesen haben.
Just in time for the Strata + Hadoop World Conference, SAS became the first software vendor to achieve ODPi Interoperability with our Base SAS® and SAS/ACCESS® Interface to Hadoop products. Now, that's a lot to digest – so let me back up a second and give some background as to what this
Tomar decisiones inteligentes a partir de Big Data Analytics se ha convertido ahora en una posibilidad real. La analítica, sin duda, ha revolucionado la manera en la que las compañías se relacionan con sus clientes y ha permitido que se adelanten para brindarles nuevas y apropiadas ofertas en el momento
Hadoop has driven an enormous amount of data analytics activity lately. And this poses a problem for many practitioners coming from the traditional relational database management system (RDBMS) world. Hadoop is well known for having lots of variety in the structure of data it stores and processes. But it's fair to
In my last post, I talked about how data still needs to be cleaned up – and data strategy still needs to be re-evaluated – as we start to work with nontraditional databases and other new technologies. There are lots of ways to use these new platforms (like Hadoop). For example, many
If your enterprise is working with Hadoop, MongoDB or other nontraditional databases, then you need to evaluate your data strategy. A data strategy must adapt to current data trends based on business requirements. So am I still the clean-up woman? The answer is YES! I still work on the quality of the data.