David Loshin, president of Knowledge Integrity, Inc., is a recognized thought leader and expert consultant in the areas of data quality, master data management and business intelligence. David is a prolific author regarding data management best practices, via the expert channel at b-eye-network.com and numerous books, white papers, and web seminars on a variety of data management best practices. His book, Business Intelligence: The Savvy Manager’s Guide (June 2003) has been hailed as a resource allowing readers to “gain an understanding of business intelligence, business management disciplines, data warehousing and how all of the pieces work together.” His book, Master Data Management, has been endorsed by data management industry leaders, and his valuable MDM insights can be reviewed at mdmbook.com . David is also the author of The Practitioner’s Guide to Data Quality Improvement. He can be reached at loshin@knowledge-integrity.com.
The concept of the internet of things (IoT) is used broadly to cover any organization of communication devices and methods, messages streaming from the device pool, data collected at a centralized point, and analysis used to exploit the combined data for business value. But this description hides the richness of
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
I've been doing some investigation into Apache Spark, and I'm particularly intrigued by the concept of the resilient distributed dataset, or RDD. According to the Apache Spark website, an RDD is “a fault-tolerant collection of elements that can be operated on in parallel.” Two aspects of the RDD are particularly
One of the challenges my clients struggle with is figuring out how to execute against a proposed data strategy. The visionaries are always happy to participate in the process of assessing the current state and proposing a vision for the future. And adding business justifications and quantifiable metrics for success
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
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
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
In my recent posts, I've been exploring the issues of integrating data that originates from beyond the organization. But this post looks at a different facet of extra-enterprise data management: data availability. In many organizations, there's a growing trend of making internal analytical data accessible to external consumers. I can
In two previous posts (Part 1 and Part 2), I explored some of the challenges of managing data beyond enterprise boundaries. These posts focused on issues around managing and governing extra-enterprise data. Let’s focus a bit on one specific challenge now – satisfying the need for business users to rapidly ingest new data sources. Sophisticated business
In a recent post, we discussed a number of factors that have expanded the reach of organizations' data management functions beyond the traditional scope of an in-house data center. Increased use of external data sources coupled with growing dependence on cloud computing have created an emerging need to exercise some level
