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At Valspar Data Management is Key to Controlling Purchasing Costs

Steve Jenkins, Global IT Director at Valspar

Steve Jenkins is working to improve information management maturity at Valspar

Raw materials costs are the company’s single largest expense category,” said Steve Jenkins, Global IT Director at Valspar, at MDM Day in London. “Data management technology can help us improve business process efficiency, manage sourcing risk and reduce RFQ cycle times.”

Valspar is a $4 billion global manufacturing company, which produces a portfolio of leading paint and coating brands. At the end of 2013, the 200 year old company celebrated record sales and earnings. They also completed two acquisitions. Valspar now has 10,000 employees operating in 25 countries.

As is the case for many global companies, growth creates complexity. “Valspar has multiple business units with varying purchasing practices. We source raw materials from 1,000s of vendors around the globe,” shared Steve.

“We want to achieve economies of scale in purchasing to control spending,” Steve said as he shared Valspar’s improvement objectives. “We want to build stronger relationships with our preferred vendors. Also, we want to develop internal process efficiencies to realize additional savings.”

Poorly managed vendor and raw materials data was impacting Valspar’s buying power

Data management at Valspar

“We realized our buying power was limited by the age and quality of available vendor and raw materials data.”

The Valspar team, who sharply focuses on productivity, had an “Aha” moment. “We realized our buying power was limited by the age and quality of available vendor data and raw materials data,” revealed Steve. 

The core vendor data and raw materials data that should have been the same across multiple systems wasn’t. Data was often missing or wrong. This made it difficult to calculate the total spend on raw materials. It was also hard to calculate the total cost of expedited freight of raw materials. So, employees used a manual, time-consuming and error-prone process to consolidate vendor data and raw materials data for reporting.

These data issues were getting in the way of achieving their improvement objectives. Valspar needed a data management solution.

Valspar needed a single trusted source of vendor and raw materials data

Informatica MDM supports vendor and raw materials data management at Valspar

The team chose Informatica MDM as their enterprise hub for vendors and raw materials

The team chose Informatica MDM, master data management (MDM) technology. It will be their enterprise hub for vendors and raw materials. It will manage this data centrally on an ongoing basis. With Informatica MDM, Valspar will have a single trusted source of vendor and raw materials data.

Informatica PowerCenter will access data from multiple source systems. Informatica Data Quality will profile the data before it goes into the hub. Then, after Informatica MDM does it’s magic, PowerCenter will deliver clean, consistent, connected and enriched data to target systems.

Better vendor and raw materials data management results in cost savings

Valspar Chameleon Jon

Valspar will gain benefits by fueling applications with clean, consistent, connected and enriched data

Valspar expects to gain the following business benefits:

  • Streamline the RFQ process to accelerate raw materials cost savings
  • Reduce the total number of raw materials SKUs and vendors
  • Increase productivity of staff focused on pulling and maintaining data
  • Leverage consistent global data visibly to:
    • increase leverage during contract negotiations
    • improve acquisition due diligence reviews
    • facilitate process standardization and reporting

 

Valspar’s vision is to tranform data and information into a trusted organizational assets

“Mastering vendor and raw materials data is Phase 1 of our vision to transform data and information into trusted organizational assets,” shared Steve. In Phase 2 the Valspar team will master customer data so they have immediate access to the total purchases of key global customers. In Phase 3, Valspar’s team will turn their attention to product or finished goods data.

Steve ended his presentation with some advice. “First, include your business counterparts in the process as early as possible. They need to own and drive the business case as well as the approval process. Also, master only the vendor and raw materials attributes required to realize the business benefit.”

Total Supplier Information Management eBook

Click here to download the Total Supplier Information Management eBook

Want more? Download the Total Supplier Information Management eBook. It covers:

  • Why your fragmented supplier data is holding you back
  • The cost of supplier data chaos
  • The warning signs you need to be looking for
  • How you can achieve Total Supplier Information Management

 

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Posted in Business/IT Collaboration, Data Integration, Data Quality, Manufacturing, Master Data Management, Operational Efficiency, PowerCenter, Vertical | Tagged , , , , , , , , , , , , , , , , , , | Leave a comment

Scalable Enterprise Analytics: Informatica PowerCenter Data Quality and Oracle Exadata

In 2012, Forbes published an article predicting an upcoming problem.

The Need for Scalable Enterprise Analytics

Specifically, increased exploration in Big Data opportunities would place pressure on the typical corporate infrastructure. The generic hardware used to run most tech industry enterprise applications was not designed to handle real-time data processing. As a result, the explosion of mobile usages, and the proliferation of social networks, was increasing the strain on the system. Most companies now faced real-time processing requirements beyond what the traditional model was designed to handle.

In the past two years, the volume of data and speed of data growth has grown significantly. As a result, the problem has become more severe. It is now clear that these challenges can’t be overcome by simply doubling or tripling their IT spending on infrastructure sprawl. Today, enterprises seek consolidated solutions that offer scalability, performance and ease of administration. The present need is for scalable enterprise analytics.

A Clear Solution Is Available

Informatica PowerCenter and Data Quality is the market leading data integration and data quality platform. This platform has now been certified by Oracle as an optimal solution for both the Oracle Exadata Database Machine and the Oracle SuperCluster.

As the high-speed on-ramp for data into Oracle Exadata, PowerCenter and Data Quality deliver up-to five times faster performance on data load, query, profiling and cleansing tasks. Informatica’s data integration customers can now easily reuse data integration code, skills and resources to access and transform any data from any data source and load it into Exadata, with the highest throughput and scalability.

Customers adopting Oracle Exadata for high-volume, high-speed analytics can now be confident with Informatica PowerCenter and Data Quality. With these products, they can ingest, cleanse and transform all types of data into Exadata with the highest performance and scale required to maximize the value of their Exadata investment.

Proving the Value of Scalable Enterprise Analytics

In order to demonstrate the efficacy of their partnership, the two companies worked together on a Proof Of Value (POV) project. The goal is to prove that using PowerCenter with Exadata would improve both performance and scalability. The project involved PowerCenter and Data Quality 9.6.1 and x4-2 Exadata Machine. Oracle 11g was considered for both standard Oracle and Exadata versions.

The first test conducted a 1TB load test to Exadata and standard Oracle in a typical PowerCenter use case. The second test consisted of querying 1TB profiling warehouse database in Data Quality use case scenario. Performance data was collected for both tests. The scalability factor was also captured. A variant of the TPCH dataset was used to generate the test data. The results were significantly higher than prior Exabyte 1TB test. In particular:

  • The data query tests achieved 5x performance.
  • The data load tests achieved a 3x-5x speed increase.
  • Linear scalability was achieved with read/write tests on Exadata.

What Business Benefits Could You Expect?

Informatica PowerCenter and Data Quality, along-with Oracle Exadata, now provide the best-of-breed combination of software and hardware, optimized to deliver the highest possible total system performance. These comprehensive tools drive agile reporting and analytics, while empowering IT organizations to meet SLAs and quality goals like never before.

  1. Extend Oracle Exadata’s access to even more business critical data sources. Utilize optimized out-of-the-box Informatica connectivity to easily access hundreds of data sources, including all the major databases, on-premise and cloud applications, mainframe, social data and Hadoop.
  2. Get more data, more quickly into Oracle Exadata. Move higher volumes of trusted data quickly into Exadata to support timely reporting with up-to-date information (i.e. up to 5x performance improvement compared to Oracle database).
  3.  Centralize management and improve insight into large scale data warehouses. Deliver the necessary insights to stakeholders with intuitive data lineage and a collaborative business glossary. Contribute to high quality business analytics, in a timely manner across the enterprise.
  4. Instantly re-direct workloads and resources to Oracle Exadata without compromising performance. Leverage existing code and programming skills to execute high-performance data integration directly on Exadata by performing push down optimization.
  5. Roll-out data integration projects faster and more cost-effectively. Customers can now leverage thousands of Informatica certified developers to execute existing data integration and quality transformations directly on Oracle Exadata, without any additional coding.
  6. Efficiently scale-up and scale-out. Customers can now maximize performance and lower the costs of data integration and quality operations of any scale by performing Informatica workload and push down optimization on Oracle Exadata.
  7.  Save significant costs involved in administration and expansion. Customers can now easily and economically manage large-scale analytics data warehousing environments with a single point of administration and control, and consolidate a multitude of servers on one rack.
  8.  Reduce risk. Customers can now leverage Informatica’s data integration and quality platform to overcome the typical performance and scalability limitations seen in databases and data storage systems. This will help reduce quality-of-service risks as data volumes rise.

Conclusion

Oracle Exadata is a well-engineered system that offers customers out-of-box scalability and performance on demand.  Informatica PowerCenter and Data Quality are optimized to run on Exadata, offering customers business benefits that speed up data integration and data quality tasks like never before.  Informatica’s certified, optimized, and purpose-built solutions for Oracle can help you enable more timely and trustworthy reporting.  You can now benefit from Informatica’s optimized solutions for Oracle Exadata to make better business decisions by unlocking the full potential of the most current and complete enterprise data available. As shown in our test results, you can attain up to 5x performance by scaling Exadata. Informatica Data Quality customers can perform profiling 1TB datasets, which is unheard before. We urge you to deploy the combined solution to solve your data integration and quality problems today while achieving high speed business analytics in these days of big data exploration and Internet Of Things.

Note:

Listen to what Ash Kulkarni, SVP, at OOW14 has to say on how @InformaticaCORP PowerCenter and Data Quality certified by Oracle as optimized for Exadata can deliver up-to five times faster performance improvement on data load, query, profiling, cleansing and mastering tasks, for Exadata.

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Posted in Data Integration, Data Integration Platform, Data Quality, Data Services, Data Warehousing, Enterprise Data Management, PowerCenter, Vibe | Tagged | Leave a comment

The Swiss Army Knife of Data Integration

The Swiss Army Knife of Data Integration

The Swiss Army Knife of Data Integration

Back in 1884, a man had a revolutionary idea; he envisioned a compact knife that was lightweight and would combine the functions of many stand-alone tools into a single tool. This idea became what the world has known for over a century as the Swiss Army Knife.

This creative thinking to solve a problem came from a request to build a soldier knife from the Swiss Army.  In the end, the solution was all about getting the right tool for the right job in the right place. In many cases soldiers didn’t need industrial strength tools, all they really needed was a compact and lightweight tool to get the job at hand done quickly.

Putting this into perspective with today’s world of Data Integration, using enterprise-class data integration tools for the smaller data integration project is over kill and typically out of reach for the smaller organization. However, these smaller data integration projects are just as important as those larger enterprise projects, and they are often the innovation behind a new way of business thinking. The traditional hand-coding approach to addressing the smaller data integration project is not-scalable, not-repeatable and prone to human error, what’s needed is a compact, flexible and powerful off-the-shelf tool.

Thankfully, over a century after the world embraced the Swiss Army Knife, someone at Informatica was paying attention to revolutionary ideas. If you’ve not yet heard the news about the Informatica platform, a version called PowerCenter Express has been released and it is free of charge so you can use it to handle an assortment of what I’d characterize as high complexity / low volume data integration challenges and experience a subset of the Informatica platform for yourself. I’d emphasize that PowerCenter Express doesn’t replace the need for Informatica’s enterprise grade products, but it is ideal for rapid prototyping, profiling data, and developing quick proof of concepts.

PowerCenter Express provides a glimpse of the evolving Informatica platform by integrating four Informatica products into a single, compact tool. There are no database dependencies and the product installs in just under 10 minutes. Much to my own surprise, I use PowerCenter express quite often going about the various aspects of my job with Informatica. I have it installed on my laptop so it travels with me wherever I go. It starts up quickly so it’s ideal for getting a little work done on an airplane. 

For example, recently I wanted to explore building some rules for an upcoming proof of concept on a plane ride home so I could claw back some personal time for my weekend. I used PowerCenter Express to profile some data and create a mapping.  And this mapping wasn’t something I needed to throw away and recreate in an enterprise version after my flight landed. Vibe, Informatica’s build once / run anywhere metadata driven architecture allows me to export a mapping I create in PowerCenter Express to one of the enterprise versions of Informatica’s products such as PowerCenter, DataQuality or Informatica Cloud.

As I alluded to earlier in this article, being a free offering I honestly didn’t expect too much from PowerCenter Express when I first started exploring it. However, due to my own positive experiences, I now like to think of PowerCenter Express as the Swiss Army Knife of Data Integration.

To start claiming back some of your personal time, get started with the free version of PowerCenter Express, found on the Informatica Marketplace at:  https://community.informatica.com/solutions/pcexpress

 Business Use Cases

Business Use Case for PowerCenter Express

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Posted in Architects, Data Integration, Data Migration, Data Transformation, Data Warehousing, PowerCenter, Vibe | Tagged , | Leave a comment

How Much is Disconnected Well Data Costing Your Business?

“Not only do we underestimate the cost for projects up to 150%, but we overestimate the revenue it will generate.” This quotation from an Energy & Petroleum (E&P) company executive illustrates the negative impact of inaccurate, inconsistent and disconnected well data and asset data on revenue potential. 

“Operational Excellence” is a common goal of many E&P company executives pursuing higher growth targets. But, inaccurate, inconsistent and disconnected well data and asset data may be holding them back. It obscures the complete picture of the well information lifecycle, making it difficult to maximize production efficiency, reduce Non-Productive Time (NPT), streamline the oilfield supply chain, calculate well by-well profitability,  and mitigate risk.

Well data expert, Stephanie Wilkin shares details about the award-winning collaboration between Noah Consulting and Devon Energy.

Well data expert, Stephanie Wilkin shares details about the award-winning collaboration between Noah Consulting and Devon Energy.

To explain how E&P companies can better manage well data and asset data, we hosted a webinar, “Attention E&P Executives: Streamlining the Well Information Lifecycle.” Our well data experts Stephanie Wilkin, Senior Principal Consultant at Noah Consulting, and Stephan Zoder, Director of Value Engineering at Informatica shared some advice. E&P companies should reevaluate “throwing more bodies at a data cleanup project twice a year.” This approach does not support the pursuit of operational excellence.

In this interview, Stephanie shares details about the award-winning collaboration between Noah Consulting and Devon Energy to create a single trusted source of well data, which is standardized and mastered.

Q. Congratulations on winning the 2014 Innovation Award, Stephanie!
A. Thanks Jakki. It was really exciting working with Devon Energy. Together we put the technology and processes in place to manage and master well data in a central location and share it with downstream systems on an ongoing basis. We were proud to win the 2014 Innovation Award for Best Enterprise Data Platform.

Q. What was the business need for mastering well data?
A. As E&P companies grow so do their needs for business-critical well data. All departments need clean, consistent and connected well data to fuel their applications. We implemented a master data management (MDM) solution for well data with the goals of improving information management, business productivity, organizational efficiency, and reporting.

Q. How long did it take to implement the MDM solution for well data?
A. The Devon Energy project kicked off in May of 2012. Within five months we built the complete solution from gathering business requirements to development and testing.

Q. What were the steps in implementing the MDM solution?
A: The first and most important step was securing buy-in on a common definition for master well data or Unique Well Identifier (UWI). The key was to create a definition that would meet the needs of various business functions. Then we built the well master, which would be consistent across various systems, such as G&G, Drilling, Production, Finance, etc. We used the Professional Petroleum Data Management Association (PPDM) data model and created more than 70 unique attributes for the well, including Lahee Class, Fluid Direction, Trajectory, Role and Business Interest.

As part of the original go-live, we had three source systems of well data and two target systems connected to the MDM solution. Over the course of the next year, we added three additional source systems and four additional target systems. We did a cross-system analysis to make sure every department has the right wells and the right data about those wells. Now the company uses MDM as the single trusted source of well data, which is standardized and mastered, to do analysis and build reports.

Q. What’s been the traditional approach for managing well data?
A. Typically when a new well is created, employees spend time entering well data into their own systems. For example, one person enters well data into the G&G application. Another person enters the same well data into the Drilling application. A third person enters the same well data into the Finance application. According to statistics, it takes about 30 minutes to enter wells into a particular financial application.

So imagine if you need to add 500 new wells to your systems. This is common after a merger or acquisition. That translates to roughly 250 hours or 6.25 weeks of employee time saved on the well create process! By automating across systems, you not only save time, you eliminate redundant data entry and possible errors in the process.

Q. That sounds like a painfully slow and error-prone process.
A. It is! But that’s only half the problem. Without a single trusted source of well data, how do you get a complete picture of your wells? When you compare the well data in the G&G system to the well data in the Drilling or Finance systems, it’s typically inconsistent and difficult to reconcile. This leads to the question, “Which one of these systems has the best version of the truth?” Employees spend too much time manually reconciling well data for reporting and decision-making.

Q. So there is a lot to be gained by better managing well data.
A. That’s right. The CFO typically loves the ROI on a master well data project. It’s a huge opportunity to save time and money, boost productivity and get more accurate reporting.

Q: What were some of the business requirements for the MDM solution?
A: We couldn’t build a solution that was narrowly focused on meeting the company’s needs today. We had to keep the future in mind. Our goal was to build a framework that was scalable and supportable as the company’s business environment changed. This allows the company to add additional data domains or attributes to the well data model at any time.

Noah Consulting's MDM Trust Framework for well data

The Noah Consulting MDM Trust Framework was used to build a single trusted source of well data

Q: Why did you choose Informatica MDM?
A: The decision to use Informatica MDM for the MDM Trust Framework came down to the following capabilities:

  • Match and Merge: With Informatica, we get a lot of flexibility. Some systems carry the API or well government ID, but some don’t. We can match and merge records differently based on the system.
  • X-References: We keep a cross-reference between all the systems. We can go back to the master well data and find out where that data came from and when. We can see where changes have occurred because Informatica MDM tracks the history and lineage.
  • Scalability: This was a key requirement. While we went live after only 5 months, we’ve been continually building out the well master based on the requiremets of the target systems.
  • Flexibility: Down the road, if we want to add an additional facet or classification to the well master, the framework allows for that.
  • Simple Integration: Instead of building point-to-point integrations, we use the hub model.

In addition to Informatica MDM, our Noah Consulting MDM Trust Framework includes Informatica PowerCenter for data integration, Informatica Data Quality for data cleansing and Informatica Data Virtualization.

Q: Can you give some examples of the business value gained by mastering well data?
A: One person said to me, “I’m so overwhelmed! We’ve never had one place to look at this well data before.” With MDM centrally managing master well data and fueling key business applications, many upstream processes can be optimized to achieve their full potential value.

People spend less time entering well data on the front end and reconciling well data on the back end. Well data is entered once and it’s automatically shared across all systems that need it. People can trust that it’s consistent across systems. Also, because the data across systems is now tied together, it provides business value they were unable to realize before, such as predictive analytics. 

Q. What’s next?
A. There’s a lot of insight that can be gained by understanding the relationships between the well, and the people, equipment and facilities associated with it. Next, we’re planning to add the operational hierarchy. For example, we’ll be able to identify which production engineer, reservoir engineer and foreman are working on a particular well.

We’ve also started gathering business requirements for equipment and facilities to be tied to each well. There’s a lot more business value on the horizon as the company streamlines their well information lifecycle and the valuable relationships around the well.

If you missed the webinar, you can watch the replay now: Attention E&P Executives: Streamlining the Well Information Lifecycle.

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Posted in Business Impact / Benefits, Data Integration, Data Quality, Enterprise Data Management, Master Data Management, Operational Efficiency, PowerCenter, Utilities & Energy | Tagged , , , , , , , | Leave a comment

Large Data Sets Experience is Needed by Computer Science Graduates

Large Data Sets Experience is Needed

Large Data Sets Experience is Needed

During recent graduate interview discussions I asked about technical items mentioned on resumes. What I heard surprised me in a couple of cases. In particular, the very low volume data sets recent graduates have worked with. I was surprised that they had not used a large data set. I got the impression that some professors do not care about the volume of data that students work with when they create their applications.

In the media there is a constant discussion about a mismatch between the skills that education provides and the capabilities graduates bring to the work place. And, whether they are prepared for work. The lack of large data set use means that skills needed by employers may be missing. I will outline the skills that could be gained by working with large data sets.

Some types of data handling are just high volume. Business intelligence and analytics consume more data than 20 years ago. Handling the increasing volume is important. Research programming and data science are truly part of big data. Even if you are not doing data science, you may be preparing and handling the data sets. Some industries and organisations just have higher volumes of data. Retail is one example. Companies that used to have less volume are obtaining more data as they adapt to the big data world. We should expect the same trend to continue with organisations that have had higher data volumes in the past. They are going to have to handle a much bigger big data experience.

There are practical aspects to  handling large data sets. These can lead to experience in storage management and design, data loading, query optimization, parallelization, bandwidth issues and data quality when large data sets are used. And when you take on those issues, architecture skills are needed and can be gained.

Today, the trends known as the Internet of Things, All Things Data, and Data First are forming. As a result there will be demand for graduates who are familiar with handling high volumes of data.

The responsibility for using a large data set falls to the student. Faculty staff need to encourage this though. They often set and guide the students’ goals. A number of large data sets that could be used by students are on the web. An example of one data set would be the Harvard Library Bibliographic Dataset available at http://openmetadata.lib.harvard.edu/bibdata. Another example is the City of Chicago that makes a number of datasets available for download in a wide range of standard formats at https://data.cityofchicago.org/. The advantage of public large data sets is the volume and the opportunity to assess the data quality of the data set. Public data sets can hold many records. They represent many more combinations than we can quickly generate by hand.  Using even a small real world data set is a vast improvement over the likely limited number of variations in self-generated data. It may be even better than using a tool to generate data. Such data when downloaded can be manipulated and used as a base for loading.

Loading large data sets is part of being prepared. It requires the use of tools. These tools can be from loaders to full data integration tool suites. A good option for students who need to load data sets is PowerCenter Express. It was announced  last year. It is free for use with up to 250,000 rows per day. It is an ideal way to experience a full enterprise data integration tool and work with significantly higher volumes.

Big Data is here and it is a growing trend. And so students need to work with larger data sets than before. It is also feasible. The tools and the data sets the students need to work with large data sets are available. Therefore, in view of the current trends, large data set use should become standard practice in computer science and related courses.

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