Ringgold Webinar Series: 4. 30-Minute Workout - Quick Tips for Better Customer Data Health
•Als PPTX, PDF herunterladen•
1 gefällt mir•1,887 views
This webinar discusses improving data quality through a data normalization and auditing process. It recommends creating a data policy, filling in missing data elements, and standardizing naming conventions. The webinar outlines a three-step process for data cleanup: 1) create a data policy, 2) fill in missing data, and 3) organize data consistently. It also describes Ringgold's auditing service which uses experts to match records to standardized identifiers and provide additional metadata. The auditing process results in clean, structured data that can enhance customer records and support business decisions.
Empfohlen
Empfohlen
Weitere ähnliche Inhalte
Ähnlich wie Ringgold Webinar Series: 4. 30-Minute Workout - Quick Tips for Better Customer Data Health
Ähnlich wie Ringgold Webinar Series: 4. 30-Minute Workout - Quick Tips for Better Customer Data Health (20)
Mehr von Ringgold Inc
Mehr von Ringgold Inc (16)
Kürzlich hochgeladen
Kürzlich hochgeladen (20)
Ringgold Webinar Series: 4. 30-Minute Workout - Quick Tips for Better Customer Data Health
- 1. Ringgold Webinar Series Session 4 February 26 2014
- 2. Today’s topic, in context Your Business Data Governance Program Healthy Records IDs
- 4. Agenda 1. Get Ready to Clean 2. Tidy Your Data in Three Steps 3. What to do Next 4. Ringgold’s Audit Service
- 5. One: Get Ready • What problem are you trying to solve? • Service issues, new journal, system migration? • Prioritize your records. • Geo, type of customer, scope of records? • Gather tools & resources. • People, information sources, time, money.
- 6. Remember…… Back up your original data, and work from a copy. Make any changes there, then re-import. Keep a copy of the pre-cleaned data in case you experience problems.
- 7. Two: Tidy Your Data in Three (Easy) Steps Really.
- 8. Step 1: Create a Data Policy Document A. Decide which elements are required Which must be filled in now as part of the cleanup effort, or for the creation of any new records B. Define each data element Make a list including all fields of a record, and define what each means (and what it doesn’t)
- 9. C. Set naming conventions To abbreviate or not to abbreviate? UCL: University College London (UK) Université Catholique de Louvain (Belgium) Universidad Cristiana Latinoamericana (Ecuador) University College Lillebælt (Denmark) Centro Universitario Celso Lisboa (Brazil) Union County Library (USA) English or Native Language?
- 10. Tip #1: Don’t reinvent the wheel Use existing authority files where possible when defining data elements or setting naming conventions ISO Country Code List (ISO 3166) UN/LOCODE for Cities Carnegie Classifications Data File Standard Identifiers (ISNI, Ringgold ID) Europa World of Learning for institution names
- 11. Tip #2: First draft only, for now.
- 12. Step 2: Fill in what is missing
- 13. Step 3: Put everything in its proper place ID 55897 Title Lt. FirstName Address 2 City 90044 State Jean LastName Company Worf High Altitude Warfare School Luc Picard 587 Capt. 55632 57741 Address1 778 North Ring Road, Gulmarg University of Birmingham Shakespeare Institute Katholieke Univ Leuven 5963 Central Departement University Road Molecularie Celbiologie Star Fleet 1 Ellipse Way Edgbaston on-Avon Dr. Beverly Crusher Leuven Com. William T. Riker Main Library Stratford Postal UK 3000 San Franisco Calif Country Title India Weaponry Weekly United States Leadership Quarterly Belgium Journal of Interspecies Bioengineering Leadership Quarterly
- 14. Three: Next Steps 1. Evangelize the data policy document 2. Encourage & enforce good data governance practices where you can 3. Keep the ball rolling….
- 15. ….and maintain good data hygiene Review new records on a regular basis Determine if additional data sets need attention Educate new staff Show tangible ROI
- 17. Going beyond a quick “spring clean” Multiple accounts for each customer Multiple internal IT systems, different divisions, methods of data capture, etc. Lack of information about which accounts are related Missing key pieces of information Lack of standard identifiers
- 18. What goes into a Ringgold audit? Database Regional & Language Expertise Defined Process Data & IT Professionals Identify
- 19. Audit Process Receive files from client Normalise data (de-duplication and automatching) Researcher checks and matches to Ringgold IDs, hierarchy etc. Researcher creates new IDs for unidentified organizations Data split into countries Data assigned to appropriate country expert Data uploaded to Identify system Client sent encrypted file via FTP with IDs and metadata
- 21. Audit deliverables Lots & lots of definitive, clean, structured data about your subscribers. A series of files which provide the complete Identify details for each of your accounts Unique Ringgold ID number Institutional hierarchy Additional metadata: size, tier, industry sector, consortia membership, alternative names, etc.
- 22. Data: Before Customer Account 39824 3994 86101 98897 90438 57700 51648 20466 79256 88279 63641 Customer Name Swets Antoni Van Leeuwenhoekhuis Christchurch School of Medicine Pohjois Karjalan Keskussairaala Keskusairalaa Pohojois Karl WFH St Joseph Torbay Hospital MHH Serials Dept. Osaka Prefectural Medical Center Osaka Furitsu Seijinbyou Ctr Address 1 Address 2 City State Info Services Aberdeen Plesmanlaan 121 Amsterdam 2 Riccarton Ave Christ Church Tikkamäentie 16 Jeonsu Tikkamäentie 16 Joensuu P.O. Box 284 Milwaukee Wisc. Newton road, Devon, Torquay, TQ2 7AA Great Britain Saueramferweg 5 Hannover 1-11-18 Chiharacho Izumi 1-9-10 Kyomachibori Habikino 1-1-50 Fukushima Nishiku Osaka Osaka PostCode AB24 3FX 1006 BE 80210 Finland 53210-9988 Country Scotland Holand New Zealand Finland 30625 Deutschland 594-1101 Japan 583-8588 JP 537-8511 Japan
- 23. Data: After Customer Account Customer Name RIN Number RIN Name RIN City RIN State RIN Country Swets 1019 University of Aberdeen 3994 Antoni Van Leeuwenhoekhuis 1228 1006 BE Netherlands www.nki.nl 86101 Christchurch School of Medicine 2494 Nederlands Kanker Instituut - Amsterdam Antoni van Leeuwenhoek Ziekenhuis University of Otago Christchurch Christchurch School of Medicine and Health Sciences 98897 Pohjois Karjalan Keskussairaala 4152 90438 Keskusairalaa Pohojois Karl 57700 RIN Type RIN Number RIN Name next level up next level up A4 academic/hos academic pital H5 1229 Institute for Research in Extramural Medicine 8140 New Zealand www.chmeds.ac. academic/me academic nz dsch M3 58994 University of Otago Faculty of Medicine Pohjois-Karjalan sairaanhoito- Joensuu ja sosiaalipalvelujen kuntayhtyma 80210 Finland www.pkssk.fi public/health public P2 4152 Pohjois-Karjalan sairaanhoito- Joensuu ja sosiaalipalvelujen kuntayhtyma 80210 Finland www.pkssk.fi public/health public P3 WFH St Joseph 5509 Wheaton Franciscan Healthcare - Saint Joseph Milwaukee 532109988 United States www.mywheaton hospital .org/stjoseph hospital H2 5510 Wheaton Franciscan Healthcare 51648 Torbay Hospital 7993 Torquay TQ2 7AA 53247 South West Strategic Health Authority 9177 79256 Serials Dept. 13608 H5 183158 Osaka Furitsu Byoin Kiko 88279 Osaka Prefectural Medical Center 13615 www.sdhct.nhs.u k www.mhhannover.de www.mch.pref.os aka.jp www.ra.opho.jp H2 MHH United Kingdom Germany hospital 20466 South Devon Healthcare NHS Foundation Trust Medizinische Hochschule Hannover Osaka Furitsu Boshi Hoken Sogo Iryo Center Osaka Furitsu Kokyuki Allergy Iryo Center H2 183158 Osaka Furitsu Byoin Kiko 63641 Osaka Furitsu Seijinbyou Ctr Osaka Furitsu Seijinbyo Center Osaka H2 183158 Osaka Furitsu Byoin Kiko WI NI 30625 Izumi 594-1101 Japan Habikino 583-8588 Japan Osaka 537-8511 Japan www.abdn.ac.uk academic RIN Sector RIN Tier academic Hannover AB24 3FX United Kingdom RIN Url 39824 53312 Aberdeen RIN Zip hospital academic/me academic dsch hospital/childr hospital en hospital hospital www.mc.pref.osa hospital ka.jp hospital M3
- 24. Auditing Use Cases Understand & analyze your customer base Disambiguate institutions & find duplicate accounts Reveal institutional relationships with hierarchies Enhance customer records with Identify metadata Support pricing decisions & policies Your audited records can act as an authority file of institutions in any system: editorial, MSS submissions, CRMs, financial, fulfillment, etc.
- 25. To sum up: It’s absolutely worth it You can do it …But you may not want to do it alone
- 26. Questions? We’d love to hear from you, and help you develop your roadmap to better data health.
- 27. Jay Henry Chief Marketing Officer www.ringgold.com Christine Orr Sales Director
Hinweis der Redaktion
- Set naming conventions for organization names, addresses, etc. As many fields as you can.Abbreviation: Once you abbreviate anything, it’s easy to start abbreviating everything. UCL example. If you must abbreviate due to fixed length fields, be very clear about what words may be abbreviated & how. (of course a standard unique identifier like ISNI or RIN, or a separate “Official Name” field, means you may not need to try to standardize all org names anyway)English vs native: Applies to cities, countries (Germany/Deutschland; Venice/Venezia, Beijing/Peking), as well as institution names. If you are an international org with staff in different countries, native may be more helpful as you are likely to be creating records in multiple languages. Just be consistent.
- You can google any of these for more information.
- You can always go back and refine this, or define additional “nice to have” fields. It is tempting to try and make the style sheet a huge part of the project, and strive for perfectionism and to cover every possible data element. Keep it to the most important bits for now, and get your project off the ground.
- Continue to improve your data, and create a periodic regular review process & schedule for new records Renewal season is a good time for this; lots of new records being added, but they are all high value records. What can you do if you get orders w no identifiable inst name? ---Push back on whoever submitted the order, ask for better information --- match on ID number (agent or your own customer number); import only new title/product order info rather than overwrite org name & address fieldsDetermine if additional data sets or records need attention – these simple steps can be applied to any data setEducate new staff on the importance of clean data. Continue to evangelize and get buy-in from those affected by poor data, or those who rely on good data to make key decisions. Show the results of your data improvement efforts (examples: time saved, revenue preserved or increased, ROI, )