There is a huge amount of buzz and hype in the market around big data. Words like Hadoop, Cassandra, Hive, NoSQL are frequently thrown around, and it can seem like they are largely detached from most people’s day-to-day reality. Particularly for folks who are doing the heavy lifting of data integration and data management for their organizations, all the buzz can seem like mere noise. I often hear comments such as:
- “We don’t do big data here. Our volumes aren’t that big.”
- “There are some folks playing around with Hadoop in the lab, but that’s about it.”
- “I think this may have potential use for us, but I’m not really sure. There’s too much hype right now. And I’m way too busy to sort through it all.” (more…)
This is the third and last post in my myth-busting series. Myth #1 was “Apps and Data Live and Die Together“. Myth #2 was “You Only Need to Focus on the Application in Any Modernization Initiative.” Now for #3.
Myth: “Big data” is just another type of data, and IT will figure out how to get it into our enterprise applications.
Fact: There is a whole new world of data out there that is waiting to be tapped for the business—data from web activity, social media interactions, mobile devices, sensors, tags—you name it. You can monitor Facebook and Twitter to understand how customers feel about your company, and link it to the products they have purchased from you. You can utilize sensor data from manufacturing equipment to improve quality control. You can track shipments on trucks and trains to dynamically optimize logistics and scheduling. (For some good research on the business opportunity of big data, check out what the folks at McKinsey & Co. have written.) (more…)
Enterprise Applications Myth #2: You Only Need to Focus on the Application in Any Modernization Initiative
This is the second in a series of myth-busting posts. Myth #1 was “Apps and Data Live and Die Together“.
Myth #2: When embarking on an application modernization initiative, either doing a significant application upgrade or entirely replacing legacy applications, you really only need to focus on the application and making sure that it aligns with your business processes.
This is the first in a series debunking three common myths about enterprise applications and the data that drives them.
Myth: Enterprise applications and the data in them live and die together.
Fact: Applications and data have different lifecycles. Sometimes the life of the data is shorter than the application. Sometimes it is longer. Either way, the friction between the two raises the cost and complexity of sustaining your applications. To get this under control, you have to have a separate approach for managing the data vs. managing the application. (more…)
Enterprise applications have been the technical foundation for running businesses for decades now. They have been the top priority for most IT organizations and consume a huge percentage of resources and budget. While they undoubtedly are critical to the business, the fact that the business is dependent on them can bring huge risk if they aren’t managed correctly. (more…)
For many of us Informatica employees, Informatica World is a whirlwind, during which it can be difficult to process all the important things that we hear from all the customers attending. Now I’ve had a couple days to digest a few things. It’s clear a lot of things have changed since the last Informatica World in 2008 with how many of our customers are thinking about data integration and information management. Some of these I was expecting. Some were surprising—in a good way.
In part one of this two-part series, I wrote about how enterprise information management (EIM) helps CIOs deliver against their top five management priorities. Now, let’s turn to the top technology areas in which CIOs are investing for the future. CIO magazine recently did a survey on “Top Tech Priorities.” The top five items that were “on the radar” or being actively researched by IT organizations were:
1. Cloud computing
2. Business intelligence
3. Business process management
4. Enterprise architecture/SOA
5. Enterprise data management
EIM plays a big role in all of these. Some are self-evident—enterprise data management is often a synonym for EIM, and the link between EIM and BI is pretty clear. But the relationship to some of the other areas may need some connecting-of-the-dots. (more…)
I was cleaning up my office last week, and I started flipping through my rather large backlog of CIO magazines. I hadn’t touched the stack in months, since I usually read the online version. But luckily I took a moment to scan the headlines, as I came across a couple items I hadn’t spent enough time on earlier: their annual State of the CIO survey, as well as a January survey regarding their “top tech priorities”.
These two surveys provided some interesting insights into the top day-to-day priorities for CIOs, as well as the future things they are keeping their eyes on. In this posting, I’ll talk about the lynchpin role enterprise information management (EIM) plays in the day-to-day running of the ship. In my next post I’ll talk about how EIM interplays with the various technologies that are at the top of the list for future investment.
From the 2010 State of the CIO survey, the top five management priorities were:
1. Aligning IT and business goals
2. Controlling IT costs
3. IT governance and portfolio management
4. Business process redesign
5. Leadership development/staff training (more…)
At Informatica, we pride ourselves on the talent and creativity in our R&D groups, and their ability to innovate. The developers work hard to understand the data challenges our customers face, and then work even harder to create the solutions that have been proven over and over again in real-world situations.
But we also know that there is a ton of data integration and data management expertise out there, beyond the boundaries of our company. Experienced developers have their bag of tips and tricks, including utilities and templates. Consultants and system integrators have accelerators, starter kits and packaged services. Other software providers have developed their own solutions to solve common data problems in the enterprise. (more…)
In my last blog, I discussed how a leading life sciences firm was starting to roll out an enterprise data management (EDM) strategy, including a strong MDM foundation. They were creating the structure and processes to manage a small number of master data elements at a global corporate level, despite a strong culture of autonomously operating business units.
Because of the independent nature of the business units, it was clear that the operational applications, including ERP, were going to continue to be managed at a business unit and regional level. And the business units were in various stages of implementing their own MDM initiatives to suit their own purposes.
So what was the goal of enforcing enterprise level master data for a few dozen key data elements? To support enterprise business intelligence. In other words, they weren’t going to try to centralize business operations. That would never work in a company of their size and complexity. The goal of enterprise data management and MDM was to maintain global visibility into key business metrics like sales by customer and inventory by product. It was really analytical MDM, rather than operational MDM.
So now I wonder—if your company is large and complex, with several different operating business units that each runs things their own way, is any corporate-level MDM initiative going to be analytical by default? Is it possible to have enterprise-wide operational MDM in decentralized organizations? Would love to hear your thoughts.