New TDWI Research Report Explores Drivers, Challenges, and Opportunities for Unified Data Warehouses and Data Lakes
        
        Report examines the convergence of the data warehouse and data lake and how organizations are using these environments together.
        
        SEATTLE, WA, June 9, 2021—TDWI Research has released its newest  Best Practices Report: Building the Unified Data Warehouse and  Data Lake. This original, survey-based report explains the  modernization and evolution of data warehouse architectures, the emergence of  the data lake, and their use together. It also provides best practices to help  organizations plan their unification strategies.
The principal author of the report, Fern Halper, is vice president and senior  director of TDWI Research for advanced analytics. She explains that enterprises  are accomplishing unification in several ways, including physical consolidation  and using semantic layers and virtualization. She offers several examples of how  enterprises are using these technologies today and explains that data lakes are  not being used as a replacement for the data warehouse but as a complementary  technology.
According to the report, “The two [technologies] have recently converged to  form a new and richer data architecture. The architecture is fairly new, and  not many organizations have embraced it yet.” The report explores the advantages  of this convergence and how enterprises can maximize its benefits.
The report’s coauthor, James Kobielus, senior director of TDWI Research for  data management, adds that nearly two-thirds of survey respondents said the  point of the unified data warehouse/data lake is to get more business value  from data, whether in operations or analytics.
Report Highlights
This comprehensive report reveals:
  - Top value drivers of the new architecture  include unifying silos (53%), providing a better foundation for analytics of  new and traditional data types (49%), and storage and cost considerations (28%)
- When consolidating the technologies, enterprises  may implement tools (such as data pipelines, data catalogs, and business  glossaries) as well as data disciplines (including data governance, master data  management, and metadata management)
- Artificial intelligence’s many use cases are the  principal driver behind the evolution of data warehouses into unified data  warehouse/data lakes
- Over a third (36%) of respondents report having  either a data warehouse or a data lake in the cloud, indicating their  mainstream acceptance
- Modern software tools (even those not  specifically designed for data governance) can assist with important practices  and help scale data governance functions across the enterprise
Today’s drive to unify data warehouses and data lakes is focused on the need  to enable data integration, interoperability, and cross-platform processes. The  TDWI report examines these drivers and explores how enterprises view these  demands as well as potential barriers that inhibit enterprises from  successfully unifying their data warehouses and data lakes.
The report concludes with 8 recommendations for successful unification and  comments about why each is important.
Platinum sponsors of this report include Denodo, Dremio, Matillion,  Snowflake Computing, Trifacta, and Vertica. Qlik was a gold sponsor of the  research.
 Download  the report here
Watch the webinar on June 22, 2021,  9:00 a.m. PT, 12:00 p.m. ET
 About the Authors
FERN HALPER is VP and senior director of TDWI Research for advanced  analytics, focusing on predictive analytics, social media analysis, text  analytics, cloud computing, and other big data analytics approaches. She has  more than 20 years of experience in data and business analysis, and has  published numerous articles on data mining and information technology. Halper  is coauthor of “Dummies” books on cloud computing, hybrid cloud,  service-oriented architecture, and service management and Big Data for Dummies. She has been a partner at industry analyst  firm Hurwitz & Associates and a lead analyst for Bell Labs. Her Ph.D. is  from Texas A&M University. You can reach her at [email protected], @fhalper on Twitter, and on LinkedIn.
JAMES KOBIELUS is senior director of TDWI Research for data management. He  is a veteran industry analyst, consultant, author, speaker, and blogger in  analytics and data management. Kobielus focuses on advanced analytics,  artificial intelligence, and cloud computing. Previously, he held positions at  Futurum Research, SiliconANGLE Wikibon, Forrester Research, Current Analysis,  and the Burton Group, and he served as senior program director, product  marketing for big data analytics, for IBM, where he was both a subject matter  expert and a strategist on thought leadership and content marketing programs  targeted at the data science community. You can reach him by email ([email protected]), on Twitter (@jameskobielus), and on LinkedIn.
About TDWI
For over 20 years, TDWI has provided  individuals and teams with a comprehensive portfolio of business and technical  education and research about all things data. TDWI’s in-depth,  best-practices-based knowledge can be quickly applied to develop world-class  talent across your organization’s business and IT functions to enhance  analytical, data-driven decision making. TDWI offers major conferences as well  as topical seminars, onsite education, membership, certification, live  webinars, resource-filled publications, industry news, and in-depth research.  See tdwi.org or follow us on  Twitter @TDWI.
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