Tag Archives: Business Intelligence
The Broken Telephone of the Data Warehouse
Jim Harris, OCDQ
In many ways, a data warehouse resembles the children’s game broken telephone, where a message is distributed across a group by being whispered into the ear of one player after another, until the last player announces the message to the entire group. Since errors typically accumulate in the retellings, the final version of the message often differs significantly from its source. Some players appear to deliberately alter what’s being said, guaranteeing a garbled message by the end of the game.
As data journeys from operational sources through the staging area, the data warehouse, the data marts, and finally into dashboards and reports, a lot could be lost in translation. As it is processed, data is often deliberately altered to make it accommodate the structure of its next target. Every time data moves from point to point, there is a possibility for semantic inconsistencies to be introduced. (more…)
The Freshest Data Makes the Best Business Decisions
There’s no denying that business continues to accelerate its pace, and that the luxury of using historical data for business intelligence (BI) and planning is quickly becoming a thing of the past. Today, businesses need immediate insight into rapidly changing data in order to survive and thrive. Data that’s even a few hours old—let alone a few days old—is largely useless. But most current information architectures today still only provide data that is a day, a week, or sometimes as much as a month old.
This leaves most BI, reporting, and analytics systems to operate without up-to-date data from operational systems, data that’s fundamental to making informed decisions about the business. To operate at the speed of business, it’s imperative that executives and decision makers have ready access to fresh information at all times, delivered continuously and automatically without impact on operational systems.
More and more organizations have found the answer in data replication. Data replication allows you to work with and make the best business decisions based on the freshest data drawn from all your operational systems. It delivers this current, up-to-date data in a seamless and non-intrusive manner, empowering you to operate at the speed of your business without constraints. It also automatically delivers this data wherever it’s needed – for operational intelligence, as well as operational use – without direct impact.
This unique “data-on-demand” approach removes the constraints of stale, old information and enables powerful outcomes for business initiatives. Fresh, current data drives new thinking across the enterprise, and can help organizations to:
- Increase revenue, delight customers, and outshine the competition
- Improve the quality and efficiency of business decisions
- Standardize on a single reliable and scalable solution that lowers costs and removes complexity
At Informatica, we’ve seen numerous customers implement Informatica Data Replication to deliver this fresh, up-to-date data for operational intelligence, reporting, and analytics, and report tremendous positive changes to their business. Some examples of customers using Informatica Data Replication with great success are:
- Westlake Financial Systems saved hundreds of thousands of dollars and improved its profitability and customer satisfaction through a more effective payment collection system
- Optus Australia increased both revenues and customer satisfaction by providing calling plan access, alerting, and self-service upgrades directly to its customer base
- A major national pharmacy chain accelerated and improved health care decision making across the business and increased agility and responsiveness to its customers, resulting in higher customer satisfaction while driving down the cost of technology
Is your business ready to make the leap to true operational intelligence using the freshest data to make your business decisions? Do you want to understand more about the impact that this kind of insight can make to your business?
If yes, please join us for a discussion with two business executives who have seen the impact in their own and their customers’ businesses using data replication on August 28 at 10 am Pacific. You can register using the link below.
Bad Business Decision? Blame Stale Data – Register Today
The freshest data does make the best business decisions. We look forward to your joining and participating in the discussion.
How Integration Platform-as-a-Service Impacts Cloud Adoption
Did you know that Forrester estimates in their 10 Cloud Predictions For 2012 blog post that on average organizations will be running more than 10 different cloud applications and that the public Software-as-a-Service (SaaS) market will hit $33 billion by the end of 2012?
However, in the same post, Forrester also acknowledged that SaaS adoption is led mainly by Customer Relationship Management (CRM), procurement, collaboration, and Human Capital Management (HCM) software and that all other software segments will “still have significantly lower SaaS adoption rates”. It’s not hard to see this in the market today, with cloud juggernaut salesforce.com leading the way in CRM, and Workday and SuccessFactors doing battle in HCM, for example. Forrester claims that amongst the lesser known software segments, Product Lifecycle Management (PLM), Business Intelligence (BI), and Supply Chain Management (SCM) will be the categories to break through as far as SaaS adoption is concerned, with approximately 25% of companies using these solutions by 2012. (more…)
Collaborative Learning in a Lean Transformation
Collaborative learning is essential for transforming work activities that involve a high degree of uncertainty and creativity into a lean value stream. These characteristics are common in enterprise integration initiatives due to unclear and inconsistent data definitions across multiple silos, rapidly changing requirements and lack of perfect knowledge around end-to-end processes. Traditional approaches generally end up propagating the integration hairball which is inefficient and wasteful – and certainly not Lean. You could say that these value streams are simply immature processes that lack standards and metrics, which is true, but the practitioners that are involved in the process don’t see it that way. They see themselves as highly skilled professionals solving complex unique problems and delivering customized solutions that fit like a glove. But yet, the outside observer who looks at the end-to-end process at the macro level sees patterns that are repeated over and over again and what appears to be a great deal of “reinventing the wheel.” (more…)
Social, Mobile, Cloud, Big Data and … Agile BI
I just came back from MicroStrategy World. There were many conversations about social, mobile, cloud and big data. There was strong interest in cloud, clear adoption of mobile, and some big data adoption. eHarmony had a great presentation about how they handle big data with Informatica, and how they’re starting to use Hadoop with Informatica HParser running on Hadoop for processing JSON.
But that wasn’t the number one conversation. The one topic that everyone was interested in – and I talked to nearly 100 customers and partners over four days – was creating new reports faster, or Agile BI. (more…)
ANNOUNCING! The 2012 Data Virtualization Architect-to-Architect & Business Value Program
Today, agility and timely visibility are critical to the business. No wonder CIO.com, states that business intelligence (BI) will be the top technology priority for CIOs in 2012. However, is your data architecture agile enough to handle these exacting demands?
In his blog Top 10 Business Intelligence Predictions For 2012, Boris Evelson of Forrester Research, Inc., states that traditional BI approaches often fall short for the two following reasons (among many others):
- BI hasn’t fully empowered information workers, who still largely depend on IT
- BI platforms, tools and applications aren’t agile enough (more…)
2012 Cloud Integration Predictions – Data, MDM, BI, Platform and IT as a Service
I spent last weekend reading Geoffrey Moore’s new book, Escape Velocity: Free Your Company’s Future from the Pull of the Past. Then on Sunday, the New York Times published this article about salesforce.com: A Leader in the Cloud Gains Rivals. Clearly “The Big Switch” is on. With this as a backdrop, the need for a comprehensive cloud data management strategy has surfaced as a top IT imperative heading into the New Year – How and when do you plan to move data to the cloud? How will you prevent SaaS silos? How will you ensure your cloud data is trustworthy, relevant and complete? What is your plan for longer-term cloud governance and control?
These are just a few of the questions you need to think through as you develop your short, medium and long-term cloud strategy. Here are my predictions for what else should be on your 2012 cloud integration radar. (more…)
Data is the Answer, Now What’s the Question? Hint: It’s The Key to Optimizing Enterprise Applications
Data quality improvement isn’t really anything new; it’s been around for some time now. Fundamentally the goal of cleansing, standardizing and enriching enterprise data through data quality processes remains the same. What’s different now, however, is that in an increasingly competitive marketplace and in difficult economic times, a complete enterprise data quality management approach can separate the leaders from the laggards. With a sound approach to enterprise data quality management, organizations reap the benefits of turning enterprise data into a key strategic asset. This helps to increase revenue, eliminate costs and reduce risks. Using the right solution, organizations can leverage data in a way never possible before, holistically and proactively, by addressing data quality issues when and where they arise. Doing so ensures key IT initiatives, like business intelligence, master data management, and enterprise applications, deliver on their promises of better business results. (more…)
Agile Data Integration Maximizes Business Value In The Era Of Big Data
Adopting Agile may require a cultural shift and in the beginning can be disruptive to an organization. However, as I mentioned in Part 1 of this blog series, Agile Data Integration holds the promise to increase chances of success, deliver projects faster, and reduce defects. Applying Lean principles within your organization can help ease the transition to Agile Data Integration. Lean is a set of principles first explored in the context of data integration by John Schmidt and David Lyle in their book on Lean Integration. First and foremost Lean recommends an organization focus on eliminating waste and optimizing the data integration process from the customers’ perspective. Agile Data Integration maximizes the business value of projects (e.g. Agile BI, Data Warehousing, Big Data Analytics, Data Migration, etc.) because you can get it right the first time by delivering exactly what the business needs when they need it. Break big projects into smaller more manageable deliverables so that you can incrementally deliver value to the business. Agile Data Integration also recommends the following: (more…)
Salesforce Integration: Information as a Competitive Advantage