Data Lakes
ⁿᵃᵗᵃˡ.ᶦⁿᵈᶦᵛᶦᵈᵘᵃˡᵒᵍᶦˢᵗ.ᶜᵒᵐ
ɪɴᴅɪᴠɪᴅᴜᴀʟᴏɢɪꜱᴛ ɴᴀᴛᴀʟ ᴄʜᴀʀᴛ
ʏᴏᴜʀ ᴀꜱᴛʀᴏʟᴏɢʏ ᴄʜᴀʀᴛ ʀᴇᴠᴇᴀʟꜱ ʏᴏᴜʀ ᴅᴇꜱᴛɪɴʏ...
ᴀ ᴄᴏᴘʏ ᴏꜰ ʏᴏᴜʀ ʙɪʀᴛʜ ᴄʜᴀʀᴛ ᴡɪʟʟ ʙᴇ ꜱᴇɴᴛ ᴛᴏ ʏᴏᴜʀ ᴇᴍᴀɪʟ ᴀᴅᴅʀᴇꜱꜱ. ᴘʟᴇᴀꜱᴇ ᴇɴᴛᴇʀ ᴀɴ ᴇᴍᴀɪʟ ᴀᴅᴅʀᴇꜱꜱ ᴛʜᴀᴛ ʏᴏᴜ ᴀᴄᴛɪᴠᴇʟʏ ᴜꜱᴇᴅ ɪɴ ᴏʀᴅᴇʀ ᴛᴏ ʀᴇᴄᴇɪᴠᴇ ʏᴏᴜʀ ꜰʀᴇᴇ ʙɪʀᴛʜ ᴄʜᴀʀᴛ ʀᴇᴀᴅɪɴɢ.
ʳᵉᶜᵉᶦᵛᵉ ᶠʳᵉᵉ ᵍᵘᶦᵈᵃⁿᶜᵉ ᵗʰʳᵒᵘᵍʰ ᵒᵘʳ ᵈᵃᶦˡʸ ʰᵒʳᵒˢᶜᵒᵖᵉ ʳᵉᵃᵈᶦⁿᵍ. ᵈᶦˢᶜᵒᵛᵉʳ ᵃᶜᶜᵘʳᵃᵗᵉ ᵖʳᵉᵈᶦᶜᵗᶦᵒⁿˢ ᵃᵇᵒᵘᵗ ʸᵒᵘʳ ᶠᵘᵗᵘʳᵉ ʷᶦᵗʰ ᵈᵃᶦˡʸ ʰᵒʳᵒˢᶜᵒᵖᵉˢ!
The concept of a data lake is less than 10 years old, but they are already hugely implemented within large companies. Their goal is to efficiently deal with ever-growing volumes of heterogeneous data, while also facing various sophisticated user needs. However, defining and building a data lake is still a challenge, as no consensus has been reached so far. Data Lakes presents recent outcomes and trends in the field of data repositories. The main topics discussed are the data-driven architecture of a data lake; the management of metadata – supplying key information about the stored data, master data and reference data; the roles of linked data and fog computing in a data lake ecosystem; and how gravity principles apply in the context of data lakes. A variety of case studies are also presented, thus providing the reader with practical examples of data lake management.
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