These: Zum Daten-MAN-gen braucht man Software. Hat man mehr Daten, nimmt man mehr Software… „Mehr vom selben!“ – jener Kulturtechnik aus der Ecke „viel hilft viel“. Stimmt das so? Man kann dies‘ knifflige Thema von verschiedenen Seiten beleuchten – im Folgenden einige mehr oder minder ernste Ansätze dazu:
In my first blog article I explained that many insurance companies have implemented a standard data model as base for their business analytics data warehouse (DWH) solutions. But why should a standard data model be more appropriate than an individual one designed especially for a certain insurance company?
A soccer fairy tale Imagine it's Soccer Saturday. You've got 10 kids and 10 loads of laundry – along with buried soccer jerseys – that you need to clean before the games begin. Oh, and you have two hours to do this. Fear not! You are a member of an advanced HOA
As I explained in Part 1 of this series, spelling my name wrong does bother me! However, life changes quickly at health insurance, healthcare and pharmaceutical companies. That said, taking unintegrated or cleansed data and propagating it to Hadoop may only help one issue. That would be the issue of getting the data
Does it upset you when you log onto your healthcare insurance portal and find that they spelled your name wrong, have your dependents listed incorrectly or your address is not correct? Well, it's definitely not a warm fuzzy feeling for me! After working for many years in the healthcare, pharmaceutical and
At a recent TDWI conference, I was strolling the exhibition floor when I noticed an interesting phenomenon. A surprising percentage of the exhibiting vendors fell into one of two product categories. One group was selling cloud-based or hosted data warehousing and/or analytics services. The other group was selling data integration products. Of
Nothing works today without an efficient data management – also in insurance business. A standard data model can be an important component of it. This article explains why. “Make or Buy”? This question has been raised very often by insurance companies planning to introduce a consistent data structure – a
Streaming analytics is a red hot topic in many industries. As the Internet of Things continues to grow, the ability to process and analyze data from new sources like sensors, mobile phones, and web clickstreams will set you apart from your competition. Event stream processing is a popular way to
In the past, we've always protected our data to create an integrated environment for reporting and analytics. And we tried to protect people from themselves when using and accessing data, which sometimes could have been considered a bottleneck in the process. We instituted guidelines and procedures around: Certification of the data
In this post, I continue the journey of getting data profiling results into SAS Visual Analytics. In my first blog I described the process of collecting DataFlux Data Quality profiling metrics to load a datamart. Now we load this datamart into memory (LASR) and then plug a VA report on
Medicare payment changes are coming. The Centers for Medicare and Medicaid Services (CMS) has announced the intention of increasing the proportion of payments to providers based on outcomes and changes in health status, as opposed to delivery of services. At the January 11th, 2016 J.P. Morgan Annual Health Care Conference,
Aktuell sprechen wir mit vielen Banken über das Management ihrer Daten. Historisch schien die Bereitstellung von Information hinlänglich gelöst: Die IT-Abteilungen stellten diverse Mart-Daten & Analyse-Tools bereit. Punkt. Banken-Daten-Management: Mehr Schein als Sein?
REpresentational State Transfer (REST) is an architectural style for designing web services that access a system's resources using HTTP methods. With the release of DataFlux Data Management 2.7 earlier this year, three new REST Application Programming Interfaces (APIs) are now available: Data Management Server Batch Jobs Data Management Server Real-time
A recent survey by Capgemini found that 78% of insurance executive interviewed cited big data analytics as the disruptive force that will have the biggest impact on the insurance industry. That’s the good news. The bad news is that unfortunately traditional data management strategies do not scale to effectively govern
This is my first blog post, and the first of a long series around Data Governance. The first thing I want to discuss is the ability to Share DataFlux Data Quality profiling metrics in SAS Visual Analytics. This post will illustrate how to extract profiling data from the DataFlux repository
Creating a strategy for the data in an organization is not a straightforward task. Not only does our business change – our software solutions also change before we can ever get done with a data strategy. So, I choose to understand that a strategy has a vision, and my vision may change
Last year at Mobile World Congress (MWC), we saw the reality of the IoT come to fruition. We saw leaders like AT&T showing their prototypes of connected cars, containers, agricultural sites, homes, etc. And it's got me wondering what we'll see at the 2016 MWC. In 2015, communications and media
In my previous post, I discussed the characteristics of a strong data strategy, the first of which was that a formal, well-defined strategy exists within your organization. This post discusses how often (and why) your organization’s data strategy needs to be updated. While strategy encompasses and sets the overall direction for
In my two prior posts, I discussed the process of developing a business justification for a data strategy and for assessing an organization's level of maturity with key data management processes and operational procedures. The business justification phase can be used to speculate about the future state of data management required
Like most boys my age at that time, I wanted to be an astronaut. Fate, however, intervened, in the form of nearsightedness, so I had to find an alternative occupation. Coming to my rescue for the launch of Apollo 11 was my father, who presented me with a huge booklet that broke
Data virtualization simplifies increasingly complex data architectures Every few months, another vendor claims one environment will replace all others. We know better. What usually happens is an elongated state of coexistence between traditional technology and the newer, sometimes disruptive one. Eventually, one technology sinks into obsolescence, but it usually takes much longer than we expect. Think of
Love includes a range of strong and positive emotional and mental states, from the highest virtue to the simplest pleasure. An example of such a wide range of meanings is the fact that the love of a mother is different from the love of a spouse, which, in turn, is
In my last post, I discussed some practical steps you can take to collect the right information for justifying why your business should design and implement a data strategy. Having identified weaknesses in your environment that could impede business success, your next step is to drill down deeper to determine where there may be
With data now impacting nearly every business activity, there should no longer be any doubt that data needs to be managed as a strategic corporate asset. This post examines the top five characteristics of a strong data strategy. Existence As I previously blogged, in today’s fast-moving business world now often takes priority
People often seek out our company for guidance related to master data management, data governance and data quality. But I see a frequent pattern, where the customer presumes that they need a particular data management solution – even if there is no specific data management problem. This approach is often triggered in reaction
The other day I was in a meeting with a client and there was an argument about who owns the data. Those arguing were IT people. In this scenario, the assumption was that data from source systems would flow into and integrate with a data warehouse. I found the discussion very interesting. Here are some of the
.@philsimon provides insights on whether a data strategy can result in competitive advantage.
In Part 1 of this series, Cheryl Doninger described how SAS Grid Manager can extend your investment in the Hadoop infrastructure. In this post, we’ll take a look at how Cloudera Manager helps Hadoop administrators meet competing service level agreements (SLAs). Cloudera Manager lets Hadoop admins set up queues to
Si se ha preguntado ¿los datos de la organización pueden contribuir al desarrollo de los lineamientos corporativos? La respuesta es sí: implementando una estrategia de Data Management. Para desarrollar y ejecutar una eficiente estrategia de Datos que esté alineada a sus objetivos de negocio, lo invitamos a seguir las siguientes recomendaciones:
.@philsimon on the need to play offense and defense with your organization's data.
