Price: $49.95 – $47.44
(as of Nov 30,2024 01:05:03 UTC – Details)
Publisher : Morgan Kaufmann; 1st edition (March 29, 2013)
Language : English
Paperback : 204 pages
ISBN-10 : 0123971675
ISBN-13 : 978-0123971678
Item Weight : 15.2 ounces
Dimensions : 7.5 x 0.46 x 9.25 inches
In today’s fast-paced business environment, managing data in motion is essential for organizations to stay competitive and make informed decisions. In our latest post, we will explore the best practice techniques and technologies for data integration, as outlined in the book “Managing Data in Motion: Data Integration Best Practice Techniques and Technologies” from The Morgan Kaufmann Series on Business Intelligence.
Data integration is the process of combining data from different sources and formats to provide a unified view for analysis and decision-making. This book covers a range of topics related to data integration, including data quality, data governance, data warehousing, and real-time data processing.
Some of the key best practice techniques highlighted in the book include:
1. Establishing a data integration strategy: It is important for organizations to have a clear strategy for data integration, including goals, objectives, and key performance indicators. This helps ensure that data integration efforts are aligned with business priorities and deliver value to the organization.
2. Implementing data quality measures: Data quality is crucial for accurate and reliable analysis. Organizations should implement data quality measures, such as data profiling, data cleansing, and data enrichment, to ensure that the data being integrated is accurate, complete, and consistent.
3. Leveraging data governance: Data governance is critical for ensuring that data is managed and used effectively within an organization. By establishing data governance policies, processes, and controls, organizations can promote data quality, security, and compliance.
4. Utilizing data warehousing: Data warehousing is a key technology for storing and managing large volumes of data for analysis. Organizations should leverage data warehousing solutions to centralize and optimize their data integration efforts.
5. Implementing real-time data processing: Real-time data processing allows organizations to process and analyze data as it is generated, enabling faster decision-making and response to changing business conditions. Organizations should leverage technologies such as stream processing and complex event processing for real-time data integration.
Overall, “Managing Data in Motion: Data Integration Best Practice Techniques and Technologies” provides valuable insights and practical guidance for organizations looking to improve their data integration capabilities. By adopting these best practice techniques and technologies, organizations can streamline their data integration processes, improve data quality, and drive better business outcomes.
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