The missing link in your data strategy – Part 2

chain with broken linkIn my last post, we touched on the importance of data migration in an overall data strategy. The reason I wanted to do this is because so many organizations see the migration of data as a technical challenge that can be outsourced and largely ignored by their internal teams. I contend that organizations have witnessed huge failures with data migration projects in the past, largely because they devolve responsibility and ignore the need for a robust approach.

The last article ended with a promise to examine how a typical data migration can feed into your data strategy. I believe there are several critical areas where data migration supports data strategy.

Read More »

Post a Comment

Assessing your data management capabilities

business meetingIn 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 opportunities to impose best practices in data management. Doing this will require you to assess your current state of data management capabilities and maturity in relation to the capabilities needed to support ongoing business needs.

Read More »

Post a Comment

Top 5 characteristics of a strong data strategy

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

contemplative manAs I previously blogged, in today’s fast-moving business world now often takes priority over later. This means operational and tactical priorities often trump strategy. Some organizations use this as an excuse for why a formal data strategy does not exist. But organizations that are too focused on today cannot capitalize on tomorrow’s opportunities. So the first and foremost characteristic of a strong data strategy is that it exists. Read More »

Post a Comment

Who owns the enterprise data? Part 2: Business

open handWhile setting up meetings with business consumers developing a data warehouse environment, I was involved in some very interesting conversations. Following are some of the assumptions that were made during these conversations, as well as a few observations. To get a well-rounded view of this topic, read my earlier post that focuses on the IT perspective. Read More »

Post a Comment

Where does Hadoop fit into an effective data strategy?

elephantIn the previous post, I described how, at least to some extent, organizations can use data to build moats around their competition. I focused on the business side of the table, although I did touch upon the need to adopt new tools to make sense of what we affectionately call big data.

Today, I'll get a bit more technical.

Read More »

Post a Comment

Business motivations for the data strategy

Puzzled business manPeople 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 to some management directive at the company, like “Move everything to Hadoop,” or “We need to be doing analytics.” It leads to the initiation of a series of projects for designing and building components or infrastructure (such as a master data management system, a data governance council or a metadata repository). Read More »

Post a Comment

Who owns the enterprise data? Part 1: IT

IT guy questioningThe 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 assumptions I noted during the debate, followed by a few observations. Read More »

Post a Comment

Can an effective data strategy help an organization build a sustainable competitive advantage?

Business people discussing data strategyIn the previous post, I argued that an effective data strategy involved playing both offense and defense. Today, I'll address whether and how such a game plan or blueprint can yield meaningful business results.

After all, that's the whole point of all this data and technology, isn't it?

Read More »

Post a Comment

SAS Grid Manager for Hadoop nicely tied into YARN (Part 2)

stones represent load balancing and SLAsIn 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 meet competing SLAs, and it enables them to manage the queues in a visual, intuitive way. For example, admins can change a queue’s configuration based on the priority of the job or the time of day. And they can rebalance based on new hardware configurations or as more load is added to the cluster.

With SAS Grid Manager for Hadoop, users can define YARN queue assignments. The default scheduler in Cloudera Manager is the Fair Scheduler. Fair Scheduler promotes fairness between competing jobs. So, if it is set up correctly, no job will have to wait too long for resources, and available resources will not be idle when existing jobs need the additional resources.

Users can also submit Hive jobs using SAS Grid Manager for Hadoop. The Hive jobs will have different SLAs, so the Hadoop administrator can create different YARN queues for it. This prevents one SAS job from taking over all the resources on the cluster. Read More »

Post a Comment