Building the Data-driven Law Firm. Questo articolo non è disponibile.
Lingua: inglese
Editore: Globe Law & Business, 2022
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- Nuovo

Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Venditore con 5 stelle
Venditore AbeBooks dal 6 gennaio 2003
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Descrizione dell’articolo da parte del venditore
2nd edition. 120 pages. 6.14x9.21x0.43 inches. In Stock.
Codice articolo zk1787429229
- Titolo
- Building the Data-driven Law Firm
- Autore
- Davies, Alex (Editor)/ Bhandarkar, Shilpa/ Donahue, Doug/ Burdon, Phil/ Fisher, David
- Editore
- Globe Law & Business
- Anno di pubblicazione
- 2022
- Condizione
- Brand New
- Rilegatura
- Paperback
- Lingua
- inglese
- ISBN 10
- 1787429229
- ISBN 13
- 9781787429222
- Edizione
- seconda edizione
- Peso dell'articolo
- 0,2 chilogrammi
Like so many other professions, law is becoming increasingly influenced by an overwhelming amount of disparate, fragmented and complex data that can both help and hinder business. Data comes from a wealth of different sources, both internal and external, constantly changing, never still. Keeping control of all that data is one challenge; leveraging it to the greater good much harder. Despite the huge amount of data in the average law firm, data-driven decision-making is relatively new and uncharted. With the hugely disruptive changes that have occurred in our ways of working over the last two years, the issue of data is now front and centre. This second edition of Building the Data-Driven Law Firm looks at how the use of data has become inextricably linked with the practice of law; how it can be utilized to the good, and the safeguards that must be put in place to mitigate the bad; how Big Data will revolutionize the way lawyers work, and the cases they will work on; and how new uses for data (including blockchain and the Internet of Things) will influence the law firm of the future. Bringing the book bang up to date, new content features how we can keep data secure in the changing world of work, how data can be used for business development and client satisfaction, the implications of data bias and data theft, and whether the way we use data is even useful anymore.
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