½ÃÀ庸°í¼­
»óǰÄÚµå
1494876

°úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ ½ÃÀå ¿¹Ãø(-2030³â) : ±¸¼º¿ä¼Òº°, Àü°³ Çüź°, Á¶Á÷ ±Ô¸ðº°, ÃÖÁ¾»ç¿ëÀÚº°, Áö¿ªº° ¼¼°è ºÐ¼®

Scientific Data Management System Market Forecasts to 2030 - Global Analysis By Component (Hardware, Software and Services), Deployment Mode, Organization Size, End User and By Geography

¹ßÇàÀÏ: | ¸®¼­Ä¡»ç: Stratistics Market Research Consulting | ÆäÀÌÁö Á¤º¸: ¿µ¹® 200+ Pages | ¹è¼Û¾È³» : 2-3ÀÏ (¿µ¾÷ÀÏ ±âÁØ)

    
    
    



¡Ø º» »óǰÀº ¿µ¹® ÀÚ·á·Î Çѱ۰ú ¿µ¹® ¸ñÂ÷¿¡ ºÒÀÏÄ¡ÇÏ´Â ³»¿ëÀÌ ÀÖÀ» °æ¿ì ¿µ¹®À» ¿ì¼±ÇÕ´Ï´Ù. Á¤È®ÇÑ °ËÅ並 À§ÇØ ¿µ¹® ¸ñÂ÷¸¦ Âü°íÇØÁֽñ⠹ٶø´Ï´Ù.

Stratistics MRC¿¡ µû¸£¸é, ¼¼°è °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ ½ÃÀåÀº 2024³â 1¾ï 6,100¸¸ ´Þ·¯ ±Ô¸ð¿¡¼­ 2030³â 15¾ï 6,660¸¸ ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹»óµÇ¸ç, ¿¹Ãø ±â°£ µ¿¾È 46.1%ÀÇ CAGR·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

°úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ(SDMS)Àº °úÇÐ µ¥ÀÌÅ͸¦ È¿À²ÀûÀ¸·Î °ü¸®, ÀúÀå ¹× °Ë»öÇÒ ¼ö ÀÖµµ·Ï ¼³°èµÈ ÅëÇÕ Ç÷§ÆûÀÔ´Ï´Ù. SDMSÀÇ ÁÖ¿ä ±â´ÉÀ¸·Î´Â ´Ù¾çÇÑ ±â±â¿¡¼­ µ¥ÀÌÅÍ ¼öÁý, ¸ÞŸµ¥ÀÌÅÍ ÁÖ¼®, ´Ù¾çÇÑ µ¥ÀÌÅÍ Çü½Ä Áö¿ø, °­·ÂÇÑ °Ë»ö ±â´É, ¹öÀü °ü¸®, ±ÔÁ¦ Ç¥ÁØ Áؼö µîÀÌ ÀÖÀ¸¸ç, °úÇÐ µ¥ÀÌÅ͸¦ È¿À²ÀûÀ¸·Î °ü¸®, ÀúÀå, °Ë»öÇÒ ¼ö ÀÖµµ·Ï ¼³°èµÈ ÅëÇÕ Ç÷§ÆûÀÔ´Ï´Ù. ¶ÇÇÑ °­·ÂÇÑ °Ë»ö ±â´É, ¹öÀü °ü¸®, ±ÔÁ¦ Ç¥ÁØ Áؼö, ¿ø½Ã µ¥ÀÌÅÍ ¼öÁýºÎÅÍ ºÐ¼®, Àå±â º¸°ü¿¡ À̸£±â±îÁö µ¥ÀÌÅÍ ¶óÀÌÇÁ»çÀÌŬ °ü¸®¸¦ Áö¿øÇÏ¿© µ¥ÀÌÅ͸¦ ÀϰüµÇ°Ô »ç¿ëÇÒ ¼ö ÀÖ°í ÃßÀûÇÒ ¼ö ÀÖµµ·Ï º¸ÀåÇÕ´Ï´Ù.

¹Ì±¹ ±¹¸³ÀÇÇеµ¼­°ü¿¡ µû¸£¸é, 2020³â 3¿ù »óÇÏÀ̱³Åë´ëÇб³ Àǰú´ëÇÐ »óÇÏÀÌ Á¾ÇÕº´¿øÀº °¨¿° ȯÀÚ Á¤¹Ð Ä¡·á¸¦ À§ÇÑ ¸ÞŸ°Ô³ð 2¼¼´ë ½ÃÄö½Ì ±â¼úÀÇ º´¿øÃ¼ ¹× À¯È¿¼º Æò°¡¸¦ À§ÇÑ 4»ó ÀÓ»ó½ÃÇèÀ» ½ÃÀÛÇß´Ù°í ÇÕ´Ï´Ù. ÀÌ·¯ÇÑ ÀÓ»ó½ÃÇèÀº ¾ÈÀüÇÑ ½ºÅ丮Áö ¼Ö·ç¼ÇÀÌ ÇÊ¿äÇÑ Áß¿äÇÑ °úÇÐ µ¥ÀÌÅ͸¦ ´ë·®À¸·Î »ý¼ºÇϱ⠶§¹®¿¡ ½ÃÀå ¼ö¿ä¸¦ ÁÖµµÇϰí ÀÖ½À´Ï´Ù.

¿¬±¸ Ȱµ¿°ú µ¥ÀÌÅÍ »ý¼ºÀÇ Áõ°¡

´Ù¾çÇÑ °úÇÐ ºÐ¾ßÀÇ ¿¬±¸°¡ °¡¼ÓÈ­µÊ¿¡ µû¶ó »ý¼ºµÇ´Â µ¥ÀÌÅÍÀÇ ¾çÀÌ ±âÇϱ޼öÀûÀ¸·Î Áõ°¡ÇÔ¿¡ µû¶ó È¿À²ÀûÀÎ µ¥ÀÌÅÍ °ü¸®, ÀúÀå ¹× ºÐ¼®À» À§ÇÑ °­·ÂÇÑ ½Ã½ºÅÛÀÌ ÇÊ¿äÇϸç, SDMS ¼Ö·ç¼ÇÀº µ¥ÀÌÅÍ ÅëÇÕ, ½Ç½Ã°£ ¾×¼¼½º, º¸¾È ½ºÅ丮Áö¿Í °°Àº Áß¿äÇÑ ±â´ÉÀ» Á¦°øÇÕ´Ï´Ù. µ¥ÀÌÅÍ ÅëÇÕ, ½Ç½Ã°£ ¾×¼¼½º, º¸¾È ½ºÅ丮Áö µîÀÇ Áß¿äÇÑ ±â´ÉÀ» Á¦°øÇϸç, Çö´ë ¿¬±¸ ȯ°æ¿¡ ÇʼöÀûÀÎ ¿ä¼Ò·Î ÀÚ¸® Àâ°í ÀÖ½À´Ï´Ù. ƯÈ÷ °Ô³ð, Á¦¾à, ȯ°æ °úÇÐ µîÀÇ ºÐ¾ß¿¡¼­ µ¥ÀÌÅÍ Áý¾àÀû ¿¬±¸°¡ ±ÞÁõÇϸ鼭 º¹ÀâÇÑ µ¥ÀÌÅÍ ¼¼Æ®¸¦ ó¸®ÇÏ´Â °í±Þ SDMS¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡Çϰí ÀÖ½À´Ï´Ù.

SDMS¸¦ µµÀÔÇϰí À¯ÁöÇÏ´Â µ¥´Â ºñ¿ëÀÌ ¸¹ÀÌ µì´Ï´Ù

SDMS ¼Ö·ç¼ÇÀÇ ±¸¸Å, Ä¿½ºÅ͸¶ÀÌ¡ ¹× ÅëÇÕ¿¡ µå´Â Ãʱ⠺ñ¿ëÀÌ ºñ½Î±â ¶§¹®¿¡ ¿¹»êÀÌ ÇÑÁ¤µÈ Áß¼Ò±Ô¸ðÀÇ ¿¬±¸±â°üÀ̳ª Çмú±â°ü¿¡¼­´Â µµÀÔ¿¡ ¾î·Á¿òÀ» °ÞÀ» ¼ö ÀÖ½À´Ï´Ù. ¶ÇÇÑ ¼ÒÇÁÆ®¿þ¾î ¾÷µ¥ÀÌÆ®, ½Ã½ºÅÛ À¯Áöº¸¼ö, Á÷¿ø ±³À°°ú °ü·ÃµÈ Áö¼ÓÀûÀÎ ºñ¿ëµµ °æÁ¦Àû ºÎ´ãÀ» °¡Áß½Ãŵ´Ï´Ù. ÀÌ·¯ÇÑ ºñ¿ëÀº ÀϺΠÁ¶Á÷¿¡¼­ SDMS¸¦ µµÀÔÇÏ´Â µ¥ ÀÖ¾î ÀÎ½ÄµÈ ÀÌÁ¡º¸´Ù ´õ Å« ºñ¿ëÀ¸·Î ÀÛ¿ëÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ½Ã½ºÅÛÀº º¹ÀâÇϱ⠶§¹®¿¡ Àü¹®ÀûÀÎ IT Áö¿øÀÌ ÇÊ¿äÇÑ °æ¿ì°¡ ¸¹À¸¸ç, ÀÌ´Â ¿î¿µ ºñ¿ëÀ» ´õ¿í Áõ°¡½Ãŵ´Ï´Ù.

µ¥ÀÌÅÍ º¸¾È, ÄÄÇöóÀ̾ð½º, Çù¾÷ÀÇ Çʿ伺

±â¹Ð¼ºÀÌ ³ôÀº ¿¬±¸ µ¥ÀÌÅÍ´Â °­·ÂÇÑ º¸È£°¡ ÇÊ¿äÇϸç, SDMS´Â HIPAA ¹× GDPR°ú °°Àº ±ÔÁ¦ Áؼö¸¦ º¸ÀåÇϱâ À§ÇØ ¾×¼¼½º Á¦¾î ¹× ¾Ïȣȭ¿Í °°Àº ±â´ÉÀ» Á¦°øÇÕ´Ï´Ù. ¶ÇÇÑ, SDMS´Â Áö¸®ÀûÀ¸·Î ºÐ»êµÈ ÆÀÀÌ ¿øÈ°ÇÏ°Ô µ¥ÀÌÅ͸¦ °øÀ¯ÇÏ°í ºÐ¼®ÇÒ ¼ö ÀÖ´Â Áß¾Ó ÁýÁᫎ Ç÷§Æû ¿ªÇÒÀ» ¼öÇàÇÔÀ¸·Î½á Çö´ë ¿¬±¸¿¡´Â Çù¾÷ÀÌ ÇʼöÀûÀÔ´Ï´Ù. À̸¦ ÅëÇØ ´õ ºü¸¥ °úÇÐ ¹ßÀü°ú Çõ½ÅÀ» ÃËÁøÇÒ ¼ö ÀÖ½À´Ï´Ù. ¿¬±¸°¡ º¹ÀâÇØÁü¿¡ µû¶ó ¾ÈÀüÇϰí Çù¾÷ÀûÀÎ µ¥ÀÌÅÍ °ü¸®¿¡ ´ëÇÑ ¼ö¿ä´Â SDMS ½ÃÀåÀ» °è¼Ó ¹ßÀü½Ãų °ÍÀ¸·Î º¸ÀÔ´Ï´Ù.

Ç¥ÁØÈ­ ºÎÁ·

µ¥ÀÌÅÍ Çü½Ä, ÇÁ·ÎÅäÄÝ, »óÈ£¿î¿ë¼º¿¡ ´ëÇÑ º¸ÆíÀûÀ¸·Î ÀÎÁ¤µÇ´Â Ç¥ÁØÀÌ ¾ø±â ¶§¹®¿¡ ´Ù¾çÇÑ ¿¬±¸ ȯ°æ¿¡ SDMS ¼Ö·ç¼ÇÀ» µµÀÔÇÒ ¶§ ÅëÇÕ ¹× ȣȯ¼º ¹®Á¦°¡ ¹ß»ýÇÕ´Ï´Ù. ÀÌ·¯ÇÑ Ç¥ÁØÈ­ÀÇ ºÎÀç´Â µ¥ÀÌÅÍ °øÀ¯, Çù¾÷, ÀÌÁ¾ ½Ã½ºÅÛ °£ÀÇ ¿øÈ°ÇÑ Á¤º¸ ±³È¯À» º¹ÀâÇÏ°Ô ¸¸µé¾î ¿¬±¸ÀÇ È¿À²¼º°ú »ý»ê¼ºÀ» ÀúÇØÇÕ´Ï´Ù. ¶ÇÇÑ, Ç¥ÁØÈ­µÈ µ¥ÀÌÅÍ °Å¹ö³Í½º ÇÁ·¹ÀÓ¿öÅ©°¡ ¾ø±â ¶§¹®¿¡ µ¥ÀÌÅÍÀÇ Ç°Áú, ¹«°á¼º, º¸¾È¿¡ Àϰü¼ºÀÌ ¾ø¾î SDMS ¼Ö·ç¼Ç¿¡ ´ëÇÑ ½Å·Ú°¡ ¶³¾îÁú ¼ö ÀÖ½À´Ï´Ù.

COVID-19ÀÇ ¿µÇâ

COVID-19·Î ÀÎÇØ ¿¬±¸±â°üµéÀÌ ¿ø°Ý Çù¾÷°ú µ¥ÀÌÅÍ °øÀ¯¸¦ ¿ì¼±¼øÀ§¿¡ µÎ¸é¼­ °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ(SDMS)ÀÇ µµÀÔÀÌ °¡¼ÓÈ­µÇ°í ÀÖ½À´Ï´Ù. ¿¬±¸½Ç°ú ¿¬±¸ ½Ã¼³¿¡ ´ëÇÑ ¹°¸®Àû Á¢±ÙÀÌ Á¦ÇѵǸ鼭 ¿ø°ÝÁö¿¡¼­ÀÇ µ¥ÀÌÅÍ Á¢±Ù°ú Çù¾÷À» ÃËÁøÇϴ Ŭ¶ó¿ìµå ±â¹Ý SDMS ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ö¿ä°¡ ±ÞÁõÇß½À´Ï´Ù. ¶ÇÇÑ, ÆÒµ¥¹ÍÀ¸·Î ÀÎÇØ µ¥ÀÌÅÍ ¹«°á¼º°ú º¸¾ÈÀÇ Á߿伺ÀÌ ºÎ°¢µÇ¸é¼­ ¿¬±¸±â°üµéÀº ÄÄÇöóÀ̾𽺸¦ ÁؼöÇÏ°í ¹Î°¨ÇÑ ¿¬±¸ µ¥ÀÌÅ͸¦ º¸È£Çϱâ À§ÇØ °­·ÂÇÑ SDMS Ç÷§Æû¿¡ ÅõÀÚÇϰí ÀÖ½À´Ï´Ù. °æÁ¦ÀûÀÎ ¾î·Á¿ò¿¡µµ ºÒ±¸Çϰí, ¿ø°Ý ¿¬±¸ Ȱµ¿À» Áö¿øÇÏ´Â È¿À²ÀûÀÎ µ¥ÀÌÅÍ °ü¸® ¼Ö·ç¼ÇÀÇ Çʿ伺Àº ÆÒµ¥¹Í ±â°£ µ¿¾È SDMS ½ÃÀåÀÇ ¼ºÀåÀ» À̲ø¾ú½À´Ï´Ù.

¿¹Ãø ±â°£ µ¿¾È Çϵå¿þ¾î ºÎ¹®ÀÌ °¡Àå Å« ºñÁßÀ» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

°í¼º´É ¼­¹ö, ½ºÅ丮Áö ½Ã½ºÅÛ, ³×Æ®¿öÅ© Àåºñ°¡ È¿À²ÀûÀÎ µ¥ÀÌÅÍ ÀúÀå, °Ë»ö, °øÀ¯¸¦ °¡´ÉÇϰÔÇÔ¿¡ µû¶ó ¿¹Ãø ±â°£ µ¿¾È Çϵå¿þ¾î°¡ ÃÖ´ëÄ¡¸¦ ±â·ÏÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ¶ÇÇÑ, ±×·¡ÇÈ Ã³¸® ÀåÄ¡(GPU) ¹× Çʵå ÇÁ·Î±×·¡¸Óºí °ÔÀÌÆ® ¾î·¹ÀÌ(FPGA)¿Í °°Àº Ư¼ö Çϵå¿þ¾î °¡¼Ó±â´Â º¹ÀâÇÑ µ¥ÀÌÅÍ ºÐ¼® ÀÛ¾÷ÀÇ °è»ê ´É·ÂÀ» Çâ»ó½Ãŵ´Ï´Ù. ó¸® ´É·Â, ½ºÅ丮Áö ¿ë·®, ³×Æ®¿öÅ© ´ë¿ªÆøÀÇ È®ÀåÀ» Æ÷ÇÔÇÑ Çϵå¿þ¾î ±â¼úÀÇ ¹ßÀüÀº ±â¼ú Çõ½ÅÀ» ÃËÁøÇÏ°í º¸´Ù °­·ÂÇϰí È®Àå °¡´ÉÇÑ SDMS ¼Ö·ç¼ÇÀÇ °³¹ßÀ» °¡´ÉÇÏ°Ô ÇÕ´Ï´Ù.

¿¹Ãø ±â°£ µ¿¾È Ŭ¶ó¿ìµå ±â¹Ý ºÎ¹®ÀÌ °¡Àå ³ôÀº CAGRÀ» ±â·ÏÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

Ŭ¶ó¿ìµå ÀÎÇÁ¶ó¸¦ Ȱ¿ëÇÏ¸é ±â¾÷Àº Çϵå¿þ¾î ¹× IT ÀÎÇÁ¶ó¿¡ ´ëÇÑ ´ë±Ô¸ð ¼±Çà ÅõÀÚ ¾øÀ̵µ ¹æ´ëÇÑ ¾çÀÇ °úÇÐ µ¥ÀÌÅ͸¦ ÀúÀå, ó¸® ¹× ºÐ¼®ÇÒ ¼ö ÀÖ½À´Ï´Ù. Ŭ¶ó¿ìµå ±â¹Ý SDMS ¼Ö·ç¼ÇÀº ¿øÈ°ÇÑ Çù¾÷, ¾îµð¼­µç µ¥ÀÌÅÍ¿¡ ´ëÇÑ ½Ç½Ã°£ ¾×¼¼½º¸¦ °¡´ÉÇÏ°Ô Çϸç, °­·ÂÇÑ ¾Ïȣȭ¿Í Á¢±Ù Á¦¾î¸¦ ÅëÇØ µ¥ÀÌÅÍ º¸¾ÈÀ» °­È­ÇÒ ¼ö ÀÖ½À´Ï´Ù. ¶ÇÇÑ, Ŭ¶ó¿ìµå Ç÷§ÆûÀÇ È®À强À» ÅëÇØ ±â¾÷Àº º¯È­ÇÏ´Â µ¥ÀÌÅÍ ¾ç°ú °è»ê ¿ä±¸»çÇ׿¡ ½±°Ô ´ëÀÀÇÒ ¼ö ÀÖ¾î °úÇÐ ¿¬±¸ÀÇ È¿À²¼º°ú Çõ½ÅÀ» ÃËÁøÇÒ ¼ö ÀÖ½À´Ï´Ù.

°¡Àå Å« Á¡À¯À²À» Â÷ÁöÇÏ´Â Áö¿ª

ºÏ¹Ì´Â ³ôÀº µðÁöÅÐ ¹®Çط°ú °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ µµÀÔÀ» ÃËÁøÇÏ´Â ±ÔÁ¤À¸·Î ÀÎÇØ ¿¹Ãø ±â°£ µ¿¾È °¡Àå Å« ½ÃÀå Á¡À¯À²À» Â÷ÁöÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ¶ÇÇÑ, TIBCO Software, Abbott Laboratories¿Í °°Àº ÁÖ¿ä ½ÃÀå ÁøÀÔÀÚµéÀÌ ÀÌ Áö¿ª¿¡ Á¸ÀçÇÑ´Ù´Â Á¡µµ ½ÃÀå ¼ºÀåÀ» ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ¶ÇÇÑ, ÇöÀç COVID-19 »çÅ·ΠÀÎÇØ ¹Ì±¹ Á¤ºÎ´Â °úÇÐ ¿¬±¸ ½Ã¼³ °£ÀÇ ¾ÈÀüÇÑ °Å¸® À¯Áö¿¡ Àû±ØÀûÀ¸·Î ³ª¼­°í ÀÖ½À´Ï´Ù. ÀÌ¿¡ µû¶ó °úÇÐ µ¥ÀÌÅ͸¦ ¾ÈÀüÇÏ°Ô ÀúÀå ¹× °ü¸®ÇÏ°í ³ëµ¿·ÂÀ» Àý°¨ÇÒ ¼ö ÀÖ´Â °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡ÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

CAGRÀÌ °¡Àå ³ôÀº Áö¿ª:

¾Æ½Ã¾ÆÅÂÆò¾çÀº ÀÇ·á »ê¾÷¿¡¼­ ½ÇÇè½Ç ÀÚµ¿È­¿¡ ´ëÇÑ ÁöÃâ Áõ°¡¿Í ±â¼úÀûÀ¸·Î Áøº¸µÈ ÀåºñÀÇ Ã¤ÅÃÀ¸·Î ÀÎÇØ ¿¹Ãø ±â°£ µ¿¾È °¡Àå ³ôÀº CAGRÀ» À¯ÁöÇÒ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ¶ÇÇÑ, °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ ¼ÒÇÁÆ®¿þ¾î¿¡ ´ëÇÑ ¼ö¿ä´Â Á¤ºÎÀÇ ÀçÁ¤ Áö¿ø°ú Àû±ØÀûÀÎ ÀÌ´Ï¼ÅÆ¼ºêÀÇ Áõ°¡·Î ÀÎÇØ Áõ°¡Çϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ Áúº´ÀÇ ³ôÀº À¯º´·üÀº ÇØ´ç Áúº´¿¡ ´ëÇÑ ½ÇÇà °¡´ÉÇÑ Ä¡·á¹ýÀ» ¹ß°ßÇÏ´Â µ¥ °ü¿©ÇÏ´Â ½ÇÇè½Ç Àü¹Ý¿¡ °ÉÃÄ ¸¹Àº ¾çÀÇ µ¥ÀÌÅ͸¦ »ý¼ºÇÕ´Ï´Ù.

¹«·á Ä¿½ºÅ͸¶ÀÌ¡ Á¦°ø:

ÀÌ º¸°í¼­¸¦ ±¸µ¶ÇÏ´Â °í°´Àº ´ÙÀ½°ú °°Àº ¹«·á ¸ÂÃãÈ­ ¿É¼Ç Áß Çϳª¸¦ ÀÌ¿ëÇÒ ¼ö ÀÖ½À´Ï´Ù.

  • ±â¾÷ °³¿ä
    • Ãß°¡ ½ÃÀå ÁøÀÔ ±â¾÷ÀÇ Á¾ÇÕÀûÀÎ ÇÁ·ÎÆÄÀϸµ(ÃÖ´ë 3°³»ç)
    • ÁÖ¿ä ±â¾÷ SWOT ºÐ¼®(ÃÖ´ë 3°³»ç)
  • Áö¿ª ¼¼ºÐÈ­
    • °í°´ÀÇ °ü½É¿¡ µû¸¥ ÁÖ¿ä ±¹°¡º° ½ÃÀå ÃßÁ¤, ¿¹Ãø, CAGR(ÁÖ: Ÿ´ç¼º °ËÅä¿¡ µû¸¥)
  • °æÀï»ç º¥Ä¡¸¶Å·
    • Á¦Ç° Æ÷Æ®Æú¸®¿À, Áö¸®Àû ÀÔÁö, Àü·«Àû Á¦ÈÞ¿¡ µû¸¥ ÁÖ¿ä ±â¾÷ º¥Ä¡¸¶Å·

¸ñÂ÷

Á¦1Àå ÁÖ¿ä ¿ä¾à

Á¦2Àå ¼­¹®

  • °³¿ä
  • ÀÌÇØ°ü°èÀÚ
  • Á¶»ç ¹üÀ§
  • Á¶»ç ¹æ¹ý
    • µ¥ÀÌÅÍ ¸¶ÀÌ´×
    • µ¥ÀÌÅÍ ºÐ¼®
    • µ¥ÀÌÅÍ °ËÁõ
    • Á¶»ç Á¢±Ù¹ý
  • Á¶»ç Á¤º¸ Ãâó
    • 1Â÷ Á¶»ç Á¤º¸ Ãâó
    • 2Â÷ Á¶»ç Á¤º¸ Ãâó
    • °¡Á¤

Á¦3Àå ½ÃÀå µ¿Ç⠺м®

  • ¼Ò°³
  • ¼ºÀå ÃËÁø¿äÀÎ
  • ¼ºÀå ¾ïÁ¦¿äÀÎ
  • ±âȸ
  • À§Çù
  • ÃÖÁ¾»ç¿ëÀÚ ºÐ¼®
  • ½ÅÈï ½ÃÀå
  • COVID-19ÀÇ ¿µÇâ

Á¦4Àå Porter's Five Forces ºÐ¼®

  • °ø±Þ ±â¾÷ÀÇ ±³¼··Â
  • ±¸¸ÅÀÚÀÇ ±³¼··Â
  • ´ëüǰÀÇ À§Çù
  • ½Å±Ô Âü¿©¾÷üÀÇ À§Çù
  • °æÀï ±â¾÷ °£ÀÇ °æÀï °ü°è

Á¦5Àå ¼¼°èÀÇ °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ ½ÃÀå : ÄÄÆ÷³ÍÆ®º°

  • ¼Ò°³
  • Çϵå¿þ¾î
  • ¼ÒÇÁÆ®¿þ¾î
  • ¼­ºñ½º

Á¦6Àå ¼¼°èÀÇ °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ ½ÃÀå : Àü°³ Çüź°

  • ¼Ò°³
  • ¿ÂÇÁ·¹¹Ì½º
  • Ŭ¶ó¿ìµå ±â¹Ý
  • ÇÏÀ̺긮µå

Á¦7Àå ¼¼°èÀÇ °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ ½ÃÀå : Á¶Á÷ ±Ô¸ðº°

  • ¼Ò°³
  • Áß¼Ò±â¾÷
  • ´ë±â¾÷

Á¦8Àå ¼¼°èÀÇ °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ ½ÃÀå : ÃÖÁ¾»ç¿ëÀÚº°

  • ¼Ò°³
  • È­ÇÐÁ¦Ç°
  • ÀǾàǰ¡¤¹ÙÀÌ¿ÀÅ×Å©³î·¯Áö
  • ½Äǰ ¹× À½·á
  • Çмú±â°ü°ú ¿¬±¸±â°ü
  • ȯ°æ °úÇÐ
  • ÀÇ·á
  • ¼®À¯ ¹× °¡½º
  • Á¦Á¶¾÷
  • ±âŸ

Á¦9Àå ¼¼°èÀÇ °úÇÐ µ¥ÀÌÅÍ °ü¸® ½Ã½ºÅÛ ½ÃÀå : Áö¿ªº°

  • ¼Ò°³
  • ºÏ¹Ì
    • ¹Ì±¹
    • ij³ª´Ù
    • ¸ß½ÃÄÚ
  • À¯·´
    • µ¶ÀÏ
    • ¿µ±¹
    • ÀÌÅ»¸®¾Æ
    • ÇÁ¶û½º
    • ½ºÆäÀÎ
    • ±âŸ À¯·´
  • ¾Æ½Ã¾ÆÅÂÆò¾ç
    • ÀϺ»
    • Áß±¹
    • Àεµ
    • È£ÁÖ
    • ´ºÁú·£µå
    • Çѱ¹
    • ±âŸ ¾Æ½Ã¾ÆÅÂÆò¾ç
  • ³²¹Ì
    • ¾Æ¸£ÇîÆ¼³ª
    • ºê¶óÁú
    • Ä¥·¹
    • ±âŸ ³²¹Ì
  • Áßµ¿ ¹× ¾ÆÇÁ¸®Ä«
    • »ç¿ìµð¾Æ¶óºñ¾Æ
    • ¾Æ¶ø¿¡¹Ì¸®Æ®
    • īŸ¸£
    • ³²¾ÆÇÁ¸®Ä«°øÈ­±¹
    • ±âŸ Áßµ¿ ¹× ¾ÆÇÁ¸®Ä«

Á¦10Àå ÁÖ¿ä °³¹ß

  • °è¾à, ÆÄÆ®³Ê½Ê, Çù¾÷, ÇÕÀÛÅõÀÚ
  • Àμö¿Í ÇÕº´
  • ½ÅÁ¦Ç° ¹ß¸Å
  • »ç¾÷ È®´ë
  • ±âŸ ÁÖ¿ä Àü·«

Á¦11Àå ±â¾÷ °³¿ä

  • Abbott Laboratories
  • Accelerated Technology Laboratories Inc
  • Advanced Chemistry Development, Inc
  • Bellefleur Physiotherapy
  • Benchling
  • Bon Secours Health System, Inc.
  • Dassault Systemes SE
  • Flywheel.io
  • LabVantage Solutions Inc
  • LabWare
  • MediaLab, Inc
  • Merck KGaA
  • SciCord LLC
  • Shimadzu Corporation
  • Sutter Health
  • Thermo Fisher Scientific Inc
  • TIBCO Software Inc
  • Uncountable Inc.
  • SuVitas
ksm 24.06.24

According to Stratistics MRC, the Global Scientific Data Management System Market is accounted for $161.0 million in 2024 and is expected to reach $1566.6 million by 2030 growing at a CAGR of 46.1% during the forecast period. A Scientific Data Management System (SDMS) is an integrated platform designed to manage, store, and retrieve scientific data efficiently. It facilitates the seamless collection, processing, and sharing of large volumes of data generated by research laboratories, ensuring data integrity and accessibility. Key features of an SDMS include data capture from various instruments, metadata annotation, and support for diverse data formats. It also provides robust search functionalities, version control, and compliance with regulatory standards. It supports data lifecycle management, from raw data acquisition to analysis and long-term archival, ensuring data is consistently available and traceable.

According to the U.S. National Library of Medicine in March 2020, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, initiated a phase-4 clinical trial to determine the pathogen and efficacy evaluation of Metagenomics second generation sequencing technology for precision therapy on the infected patients. These clinical trials also generate significant amount of crucial scientific data that requires secure storage solutions thereby, driving the demand for the market.

Market Dynamics:

Driver:

Increased research activity and data generation

As research in various scientific fields accelerates, the volume of data generated rises exponentially, necessitating robust systems for efficient data management, storage, and analysis. SDMS solutions offer critical functionalities such as data integration, real-time access, and secure storage, making them indispensable for modern research environments. The surge in data-intensive research, particularly in fields like genomics, pharmaceuticals, and environmental sciences, amplifies the demand for advanced SDMS to handle complex datasets.

Restraint:

Implementing and maintaining SDMS can be expensive

The high initial costs of purchasing, customizing, and integrating SDMS solutions can deter small to mid-sized research organizations and academic institutions with limited budgets. Additionally, ongoing expenses related to software updates, system maintenance, and staff training add to the financial burden. These costs may outweigh perceived benefits for some organizations, leading to resistance in adopting SDMS. The complexity of these systems often requires specialized IT support, further increasing operational expenses.

Opportunity:

Need for data security, compliance, and collaboration

Sensitive research data requires robust protection, and SDMS offer features like access controls and encryption to ensure compliance with regulations like HIPAA and GDPR. Additionally, collaboration is crucial in modern research. SDMS act as centralized platforms, enabling geographically spread teams to seamlessly share and analyze data. This fosters faster scientific progress and innovation. As research complexity grows, the demand for secure and collaborative data management will continue to propel the SDMS market forward.

Threat:

Lack of Standardization

Without universally accepted standards for data formats, protocols, and interoperability, integration and compatibility issues arise when implementing SDMS solutions across different research environments. This lack of standardization complicates data sharing, collaboration, and the seamless exchange of information between disparate systems, hindering research efficiency and productivity. Furthermore, the absence of standardized data governance frameworks can lead to inconsistencies in data quality, integrity, and security, eroding trust in SDMS solutions.

Covid-19 Impact

The COVID-19 pandemic has accelerated the adoption of Scientific Data Management Systems (SDMS) as research organizations prioritize remote collaboration and data sharing. With restrictions on physical access to laboratories and research facilities, demand for cloud-based SDMS solutions surged to facilitate remote data access and collaboration. Additionally, the pandemic highlighted the importance of data integrity and security, prompting organizations to invest in robust SDMS platforms to ensure compliance and protect sensitive research data. Despite economic challenges, the need for efficient data management solutions to support remote research activities has bolstered the growth of the SDMS market during the pandemic.

The hardware segment is expected to be the largest during the forecast period

The hardware is expected to be the largest during the forecast period owing to high-performance servers, storage systems, and networking equipment enable efficient data storage, retrieval, and sharing. Additionally, specialized hardware accelerators, such as graphical processing units (GPUs) and field-programmable gate arrays (FPGAs), enhance computational capabilities for complex data analysis tasks. Advancements in hardware technology, including increased processing power, storage capacity, and network bandwidth, drive innovation and enable the development of more robust and scalable SDMS solutions.

The cloud-based segment is expected to have the highest CAGR during the forecast period

The cloud-based segment is expected to have the highest CAGR during the forecast period, by leveraging cloud infrastructure, organizations can store, process, and analyze vast amounts of scientific data without the need for significant upfront investments in hardware and IT infrastructure. Cloud-based SDMS solutions enable seamless collaboration, real-time access to data from anywhere, and enhanced data security through robust encryption and access controls. Moreover, the scalability of cloud platforms allows organizations to easily accommodate fluctuating data volumes and computational requirements, driving efficiency and innovation in scientific research.

Region with largest share:

North America is projected to hold the largest market share during the forecast period because of its high digital literacy and rules that promote the adoption of a scientific data management system. Also, the presence of significant market players in the regions, such as TIBCO Software and Abbott Laboratories, is fueling the market growth. In addition, amid the current COVID-19 epidemic, the US government has aggressively concentrated on keeping safe-distance even among scientific research facilities. This is expected to increase demand for scientific data management systems to securely store and manage scientific data while reducing the requirement for labor.

Region with highest CAGR:

Asia Pacific is projected to hold the highest CAGR over the forecast period due to growing expenditures in the healthcare industry for lab automation and the adoption of technologically advanced equipment. Also, the need for scientific data management system software is increasing as a result of rising government financing and positive initiatives. The high prevalence of these disorders creates a massive quantity of data across the research laboratories involved in discovering viable treatments for the condition.

Key players in the market

Some of the key players in Scientific Data Management System market include Abbott Laboratories, Accelerated Technology Laboratories Inc, Advanced Chemistry Development, Inc, Bellefleur Physiotherapy, Benchling, Bon Secours Health System, Inc., Dassault Systemes SE, Flywheel.io, LabVantage Solutions Inc, LabWare, MediaLab, Inc, Merck KGaA, SciCord LLC, Shimadzu Corporation, Sutter Health, Thermo Fisher Scientific Inc, TIBCO Software Inc, Uncountable Inc. and SuVitas

Key Developments:

In May 2024, JLR and Dassault Systemes Extend Partnership, Deploying the 3DEXPERIENCE Platform for All Vehicle Programs Worldwide. The 3DEXPERIENCE platform connects all stakeholders in one collaborative virtual environment, leveraging the latest technological innovation

In March 2024, Abbott, Real Madrid and the Real Madrid Foundation announced today the extension of their partnership through Real Madrid's 2026-27 season. Abbott will remain Global Health Sciences and Nutrition Partner of Real Madrid Football Club and Global Partner of the Real Madrid Foundation.

In January 2024, Abbott announced the launch of its new PROTALITY(TM) brand. The high-protein nutrition shake is the first product in this line to support the growing number of adults interested in pursuing weight loss while maintaining muscle mass and good nutrition.

Components Covered:

  • Hardware
  • Software
  • Services

Deployment Modes Covered:

  • On-Premises
  • Cloud-Based
  • Hybrid

Organization Sizes Covered:

  • Small and Medium-sized Enterprises (SMEs)
  • Large Enterprises

End Users Covered:

  • Chemicals
  • Pharmaceuticals & Biotechnology
  • Food & Beverage
  • Academia and Research Institutes
  • Environmental Science
  • Healthcare
  • Oil and Gas
  • Manufacturing
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 End User Analysis
  • 3.7 Emerging Markets
  • 3.8 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Scientific Data Management System Market, By Component

  • 5.1 Introduction
  • 5.2 Hardware
  • 5.3 Software
  • 5.4 Services

6 Global Scientific Data Management System Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 On-Premises
  • 6.3 Cloud-Based
  • 6.4 Hybrid

7 Global Scientific Data Management System Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Small and Medium-sized Enterprises (SMEs)
  • 7.3 Large Enterprises

8 Global Scientific Data Management System Market, By End User

  • 8.1 Introduction
  • 8.2 Chemicals
  • 8.3 Pharmaceuticals & Biotechnology
  • 8.4 Food & Beverage
  • 8.5 Academia and Research Institutes
  • 8.6 Environmental Science
  • 8.7 Healthcare
  • 8.8 Oil and Gas
  • 8.9 Manufacturing
  • 8.10 Other End Users

9 Global Scientific Data Management System Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Abbott Laboratories
  • 11.2 Accelerated Technology Laboratories Inc
  • 11.3 Advanced Chemistry Development, Inc
  • 11.4 Bellefleur Physiotherapy
  • 11.5 Benchling
  • 11.6 Bon Secours Health System, Inc.
  • 11.7 Dassault Systemes SE
  • 11.8 Flywheel.io
  • 11.9 LabVantage Solutions Inc
  • 11.10 LabWare
  • 11.11 MediaLab, Inc
  • 11.12 Merck KGaA
  • 11.13 SciCord LLC
  • 11.14 Shimadzu Corporation
  • 11.15 Sutter Health
  • 11.16 Thermo Fisher Scientific Inc
  • 11.17 TIBCO Software Inc
  • 11.18 Uncountable Inc.
  • 11.19 SuVitas
»ùÇà ¿äû ¸ñ·Ï
0 °ÇÀÇ »óǰÀ» ¼±Åà Áß
¸ñ·Ï º¸±â
Àüü»èÁ¦