½ÃÀ庸°í¼­
»óǰÄÚµå
1530886

Åë½Å ¾Ö³Î¸®Æ½½º ½ÃÀå ¿¹Ãø(-2030³â) : ÄÄÆ÷³ÍÆ®º°, µµÀÔ, ±â¾÷ ±Ô¸ðº°, ¿ëµµº°, ÃÖÁ¾»ç¿ëÀÚº°, Áö¿ªº° ¼¼°è ºÐ¼®

Telecom Analytics Market Forecasts to 2030 - Global Analysis By Component, Deployment, Enterprise Size, Application, 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°èÀÇ Åë½Å ¾Ö³Î¸®Æ½½º ½ÃÀåÀº 2024³â¿¡ 78¾ï ´Þ·¯¸¦ Â÷ÁöÇÏ°í ¿¹Ãø ±â°£ Áß CAGRÀº 16.5%·Î ¼ºÀåÇϸç, 2030³â¿¡´Â 194¾ï ´Þ·¯¿¡ ´ÞÇÒ Àü¸ÁÀÔ´Ï´Ù.

Åë½Å ¾Ö³Î¸®Æ½½º´Â Åë½Å ³×Æ®¿öÅ©¿Í ½Ã½ºÅÛ¿¡¼­ µ¥ÀÌÅ͸¦ ¼öÁý, ÇØ¼®, Àû¿ëÇÏ¿© ¿î¿µÀ» ÃÖÀûÈ­ÇÏ°í ¼­ºñ½º Á¦°øÀ» °­È­ÇÏ´Â °úÁ¤À» ¸»ÇÕ´Ï´Ù. ¿©±â¿¡´Â ÅëÈ­ ±â·Ï, ³×Æ®¿öÅ© ¼º´É ÁöÇ¥, °í°´°úÀÇ »óÈ£ ÀÛ¿ë µî¿¡¼­ »ý¼ºµÇ´Â ¹æ´ëÇÑ ¾çÀÇ µ¥ÀÌÅ͸¦ °í±Þ ºÐ¼® ±â¼ú ¹× ÅøÀ» »ç¿ëÇÏ¿© ºÐ¼®ÇÏ´Â °ÍÀÌ Æ÷ÇԵ˴ϴÙ. Åë½Å ¾Ö³Î¸®Æ½½º´Â ±â¾÷ÀÌ ³×Æ®¿öÅ© È¿À²¼ºÀ» °³¼±Çϰí, ¼­ºñ½º Áß´ÜÀ» ¿¹Ãø ¹× ¹æÁöÇϸç, °í°´ ÇൿÀ» ÀÌÇØÇÏ¿© Ÿ±êÆÃµÈ ¸¶ÄÉÆÃÀ» ¼öÇàÇϰí, ¸®¼Ò½º ¹èºÐÀ» ÃÖÀûÈ­ÇÒ ¼ö ÀÖ´Â ½Ç¿ëÀûÀÎ ÀλçÀÌÆ®À» ÃßÃâÇÒ ¼ö ÀÖµµ·Ï µµ¿ÍÁÝ´Ï´Ù.

Statista°¡ 2022³â ¹Ì±¹¿¡¼­ ½Ç½ÃÇÑ 'Global Consumer Survey' Á¶»ç¿¡ µû¸£¸é ÀÀ´äÀÚÀÇ 44%´Â ÆÄÀϰú À̹ÌÁö¿¡ ¿Â¶óÀÎ ½ºÅ丮Áö¸¦ »ç¿ëÇϰí ÀÖÀ¸¸ç, 40%´Â ¿ÀÇǽº ¹®¼­ ÀÛ¼º¿¡ ¿Â¶óÀÎ ¿ëµµÀ» »ç¿ëÇϰí ÀÖ´Â °ÍÀ¸·Î ³ªÅ¸³µ½À´Ï´Ù. °ÍÀ¸·Î ³ªÅ¸³µ½À´Ï´Ù.

°¡ÀÔÀÚ ÀλçÀÌÆ®¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡

Telecom AnalyticsÀÇ °¡ÀÔÀÚ ÀλçÀÌÆ®¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡´Â Åë½Å ¾÷°è¿¡¼­ µ¥ÀÌÅͺ£À̽º ÀÇ»ç°áÁ¤¿¡ ´ëÇÑ ÀνÄÀÌ ³ô¾ÆÁø °ÍÀ» ¹Ý¿µÇÕ´Ï´Ù. Åë½Å»çµéÀº °¡ÀÔÀÚÀÇ Çൿ, ¼±È£µµ, µ¿Çâ¿¡ ´ëÇÑ ½ÉÃþÀûÀÎ ÀÌÇØ¸¦ À§ÇØ °í±Þ ºÐ¼®À» Ȱ¿ëÇϰí ÀÖ½À´Ï´Ù. °í°´°úÀÇ »óÈ£ ÀÛ¿ë, ¼­ºñ½º »ç¿ë, ³×Æ®¿öÅ© ¼º´É¿¡¼­ »ý¼ºµÇ´Â ¹æ´ëÇÑ ¾çÀÇ µ¥ÀÌÅ͸¦ ºÐ¼®ÇÏ¿© ¼­ºñ½º °³ÀÎÈ­, ³×Æ®¿öÅ© ¸®¼Ò½º ÃÖÀûÈ­ ¹× Àü¹ÝÀûÀÎ °í°´ °æÇèÀ» °³¼±ÇÒ ¼ö ÀÖ´Â ÀλçÀÌÆ®À» È®º¸ÇÒ ¼ö ÀÖ°Ô µÇ¾ú½À´Ï´Ù.

µ¥ÀÌÅÍ ÇÁ¶óÀ̹ö½Ã ¹× º¸¾È¿¡ ´ëÇÑ ¿ì·Á

µ¥ÀÌÅÍ ÇÁ¶óÀ̹ö½Ã ¹× º¸¾È¿¡ ´ëÇÑ ¿ì·Á´Â ±ÍÁßÇÑ °í°´ Á¤º¸¿¡ ´ëÇÑ Á¢±ÙÀ» Á¦ÇÑÇÏ°í µ¥ÀÌÅͺ£À̽º ÀλçÀÌÆ®À» ¹æÇØÇÔÀ¸·Î½á Åë½Å ¾Ö³Î¸®Æ½½º¿¡ Å« ¿µÇâÀ» ¹ÌĨ´Ï´Ù. Åë½Å »ç¾÷ÀÚµéÀº ¼­ºñ½º ÃÖÀûÈ­, µ¿Çâ ¿¹Ãø, »ç¿ëÀÚ °æÇè °³¼±À» À§ÇØ ¹æ´ëÇÑ ¾çÀÇ °í°´ µ¥ÀÌÅÍ ºÐ¼®¿¡ Å©°Ô ÀÇÁ¸Çϰí ÀÖ½À´Ï´Ù. ±×·¯³ª GDPR(EU °³ÀÎÁ¤º¸º¸È£±ÔÁ¤)À̳ª CCPA¿Í °°Àº ¾ö°ÝÇÑ µ¥ÀÌÅÍ º¸È£ ±ÔÁ¤Àº À§¹ÝÀ̳ª ¾Ç¿ëÀ» ¹æÁöÇϱâ À§ÇØ µ¥ÀÌÅ͸¦ ¾ö°ÝÇÏ°Ô Ãë±ÞÇÏ°í º¸°üÇØ¾ß ÇÕ´Ï´Ù. ÀÌ·¯ÇÑ ±ÔÁ¤ Áؼö´Â Á¾Á¾ º¹ÀâÇÑ ¾Ïȣȭ ¹æ½Ä°ú µ¥ÀÌÅÍ ¾×¼¼½º Á¦ÇÑÀ» ¼ö¹ÝÇϸç, ÀÌ´Â ºÐ¼®ÀÇ ÆøÀ» Á¼È÷°í ÀÇ»ç°áÁ¤ °úÁ¤À» ´À¸®°Ô ¸¸µé ¼ö ÀÖ½À´Ï´Ù.

¿¹Ãø ºÐ¼®¿¡ ´ëÇÑ ¼ö¿ä Áõ°¡

Åë½Å »ê¾÷¿¡¼­ ¿¹Ãø ºÐ¼®¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡ÇÔ¿¡ µû¶ó ±â¾÷ÀÇ »ç¾÷ ¿î¿µ°ú °í°´ ¼­ºñ½º ¹æ½ÄÀÌ º¯È­Çϰí ÀÖ½À´Ï´Ù. ¿¹Ãø ºÐ¼®Àº µ¥ÀÌÅÍ ¸¶ÀÌ´×, ¸Ó½Å·¯´×, Åë°è ¾Ë°í¸®ÁòÀ» Ȱ¿ëÇÏ¿© °ú°Å µ¥ÀÌÅ͸¦ ºÐ¼®ÇÏ¿© ¹Ì·¡ÀÇ »ç°Ç°ú ÇൿÀ» ¿¹ÃøÇÕ´Ï´Ù. Åë½Å ¾÷°è¿¡¼­ ÀÌ´Â º¸´Ù °³ÀÎÈ­µÈ °í°´ °æÇè, ³×Æ®¿öÅ© °ü¸® °³¼±, ¾÷¹« È¿À²¼º Çâ»óÀ¸·Î À̾îÁý´Ï´Ù. Åë½Å»ç´Â °í°´ÀÇ Çൿ ÆÐÅÏÀ» ºÐ¼®ÇÏ¿© ÇØÁö¸¦ ¿¹ÃøÇϰí, ¸¶ÄÉÆÃ Àü·«À» Á¶Á¤Çϰí, Ÿ±êÆÃµÈ ÇÁ·Î¸ð¼ÇÀ» Á¦°øÇÒ ¼ö ÀÖ½À´Ï´Ù.

µ¥ÀÌÅÍ ÅëÇÕÀÇ º¹À⼺

Åë½Å ¾Ö³Î¸®Æ½½ºÀÇ µ¥ÀÌÅÍ ÅëÇÕÀº °ü·Ã µ¥ÀÌÅÍ ¼Ò½º°¡ ¹æ´ëÇÏ°í ´Ù¾çÇϹǷΠº¹ÀâÇÕ´Ï´Ù. Åë½Å »ç¾÷ÀÚ´Â °í°´°úÀÇ »óÈ£ ÀÛ¿ë, ³×Æ®¿öÅ© ¼º´É ÁöÇ¥, û±¸ Á¤º¸, ¼­ºñ½º »ç¿ë ÆÐÅÏ µî ´Ù¾çÇÑ À¯ÇüÀÇ µ¥ÀÌÅ͸¦ °ü¸®Çϰí ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ µ¥ÀÌÅÍ ¼Ò½º´Â Á¾Á¾ ¼­·Î ´Ù¸¥ Çü½Ä, ±¸Á¶, Ç¥ÁØÀ» °¡Áø À̱âÁ¾ ½Ã½ºÅÛ¿¡ ÀúÀåµÇ´Â °æ¿ì°¡ ¸¹½À´Ï´Ù. ÀÌ·¯ÇÑ µ¥ÀÌÅ͸¦ ÅëÇÕÇÏ·Á¸é Àϰü¼º, Á¤È®¼º, Àû½Ã¼ºÀ» º¸ÀåÇϱâ À§ÇØ ¸¹Àº ³ë·ÂÀÌ ÇÊ¿äÇÕ´Ï´Ù. ±×·¯³ª °ú°Å µ¥ÀÌÅÍ¿Í ½Ç½Ã°£ ÀÔ·ÂÀ» ÅëÇÕÇϰí, µ¥ÀÌÅÍ Ç°Áú ¹®Á¦¸¦ ÇØ°áÇϰí, °³ÀÎ Á¤º¸ º¸È£ ¹× º¸¾È Ç¥ÁØÀ» À¯ÁöÇØ¾ß ÇϹǷΠ¹®Á¦´Â ´õ¿í º¹ÀâÇØÁý´Ï´Ù.

COVID-19ÀÇ ¿µÇâ :

COVID-19´Â µðÁöÅÐ ÀüȯÀ» °¡¼ÓÈ­Çϰí ÀÌ¿ë ÆÐÅÏÀ» º¯È­½ÃÅ´À¸·Î½á Åë½Å ¾Ö³Î¸®Æ½½º¿¡ Å« ¿µÇâÀ» ¹ÌÃÆ½À´Ï´Ù. ºÀ¼â·ÉÀÌ ³»·ÁÁö°í ¿ø°Ý ±Ù¹«°¡ º¸ÆíÈ­µÇ¸é¼­ ÀÎÅͳݰú ¸ð¹ÙÀÏ µ¥ÀÌÅÍ ¼Òºñ°¡ ±ÞÁõÇß°í, Åë½Å»çµéÀº ³×Æ®¿öÅ© ¿ë·®°ú ¼­ºñ½º ³»¿ëÀ» Àç°ËÅäÇØ¾ß ÇÏ´Â »óȲ¿¡ Á÷¸éÇß½À´Ï´Ù. ºÐ¼®Àº ÀÌ·¯ÇÑ ±ÞÁõÀ» °ü¸®ÇÏ´Â µ¥ ÀÖÀ¸¸ç, ¸Å¿ì Áß¿äÇÑ ¿ªÇÒÀ» ÇßÀ¸¸ç, Åë½Å»ç°¡ ³×Æ®¿öÅ© ¼º´ÉÀ» ÃÖÀûÈ­ÇÏ°í Æ®·¡ÇÈ ±ÞÁõÀ» ¿¹ÃøÇÏ°í °í°´ °æÇèÀ» °³¼±ÇÏ´Â µ¥ µµ¿òÀÌ µÇ¾ú½À´Ï´Ù. ÆÒµ¥¹ÍÀ¸·Î ÀÎÇØ µðÁöÅÐ Á¢±ÙÀÇ °ÝÂ÷°¡ µå·¯³µ°í, ¿¬°á °ÝÂ÷ ÇØ¼Ò¿¡ ´ëÇÑ °ü½ÉÀÌ ³ô¾ÆÁ³½À´Ï´Ù.

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

Çϵå¿þ¾î ºÎ¹®Àº ³×Æ®¿öÅ© ÀÎÇÁ¶ó¿¡ ÷´Ü ±â¼ú°ú °í¼º´É ÄÄÆ÷³ÍÆ®¸¦ ÅëÇÕÇÔÀ¸·Î½á ¿¹Ãø ±â°£ Áß °¡Àå Å« ¼ºÀå¼¼¸¦ º¸ÀÏ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ÃֽŠÅë½Å ¾Ö³Î¸®Æ½½º´Â ½Ç½Ã°£ µ¥ÀÌÅÍ Ã³¸® ¹× ºÐ¼®¿¡ Å©°Ô ÀÇÁ¸Çϰí ÀÖÀ¸¸ç, À̸¦ À§Çؼ­´Â ÀúÁö¿¬À¸·Î ¹æ´ëÇÑ ¾çÀÇ µ¥ÀÌÅ͸¦ ó¸®ÇÒ ¼ö ÀÖ´Â °ß°íÇÑ Çϵå¿þ¾î ¼Ö·ç¼ÇÀÌ ÇÊ¿äÇÕ´Ï´Ù. º¹ÀâÇÑ ³×Æ®¿öÅ© µ¥ÀÌÅÍ ½ºÆ®¸²À» °ü¸®Çϰí ÇØ¼®Çϱâ À§Çؼ­´Â Çâ»óµÈ ¼­¹ö, Àü¿ë ÇÁ·Î¼¼¼­, ´ë¿ë·® ½ºÅ丮Áö ½Ã½ºÅÛÀÌ ÇʼöÀûÀÔ´Ï´Ù. ÀÌ·¯ÇÑ ¹ßÀüÀ» ÅëÇØ Åë½Å »ç¾÷ÀÚ´Â ³×Æ®¿öÅ© ¼º´ÉÀ» °³¼±Çϰí, ¸®¼Ò½º ÇÒ´çÀ» ÃÖÀûÈ­Çϸç, °í°´ °æÇèÀ» Çâ»ó½ÃŰ´Â °í±Þ ºÐ¼® ¾Ë°í¸®ÁòÀ» ±¸ÇöÇÒ ¼ö ÀÖ½À´Ï´Ù.

¿¹Ãø ±â°£ Áß ³×Æ®¿öÅ© ºÐ¼® ºÐ¾ß°¡ °¡Àå ³ôÀº CAGRÀ» ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù.

³×Æ®¿öÅ© ºÐ¼® ºÐ¾ß´Â ¿¹Ãø ±â°£ Áß °¡Àå ³ôÀº CAGRÀ» ³ªÅ¸³¾ °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. ³×Æ®¿öÅ© ºÐ¼®Àº ³×Æ®¿öÅ© ¼º´É°ú °í°´ Çൿ¿¡ ´ëÇÑ ´õ ±íÀº ÀλçÀÌÆ®À» Á¦°øÇÔÀ¸·Î½á Åë½Å ¾Ö³Î¸®Æ½½º¿¡ Çõ¸íÀ» ÀÏÀ¸Å°°í ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ °­È­¿¡´Â °í±Þ µ¥ÀÌÅÍ ºÐ¼®°ú ¸Ó½Å·¯´×À» »ç¿ëÇÏ¿© ³×Æ®¿öÅ© ¿î¿µÀ» ½Ç½Ã°£À¸·Î ¸ð´ÏÅ͸µÇϰí ÃÖÀûÈ­ÇÏ´Â °ÍÀÌ Æ÷ÇԵ˴ϴÙ. ¹æ´ëÇÑ ¾çÀÇ ³×Æ®¿öÅ© µ¥ÀÌÅ͸¦ ºÐ¼®ÇÔÀ¸·Î½á Åë½Å ¾Ö³Î¸®Æ½½º´Â ÆÐÅÏÀ» ½Äº°Çϰí, ÀáÀçÀûÀÎ ¹®Á¦¸¦ ¿¹ÃøÇϰí, ÀÇ»ç°áÁ¤À» °³¼±ÇÒ ¼ö ÀÖ½À´Ï´Ù. ¶ÇÇÑ º¸´Ù È¿À²ÀûÀÎ ³×Æ®¿öÅ© °ü¸®, ´Ù¿îŸÀÓ °¨¼Ò, »ç¿ëÀÚ¿¡ ´ëÇÑ ¼­ºñ½º ǰÁú Çâ»óÀ¸·Î À̾îÁú ¼ö ÀÖ½À´Ï´Ù. Åë½Å »ç¾÷ÀÚ¿¡°Ô ³×Æ®¿öÅ© ºÐ¼®Àº »çÀü ¿¹¹æÀû À¯Áöº¸¼ö, ´õ ³ªÀº ¸®¼Ò½º ¹èºÐ, ¸ñÇ¥ ÁöÇâÀû °³¼±À» °¡´ÉÇÏ°Ô Çϸç, ÀÌ ¸ðµç °ÍÀÌ ¿ì¼öÇÑ °í°´ °æÇè¿¡ ±â¿©ÇÕ´Ï´Ù.

°¡Àå Å« Á¡À¯À²À» Â÷ÁöÇÏ´Â Áö¿ª

¿¹Ãø ±â°£ Áß ºÏ¹Ì°¡ °¡Àå Å« ½ÃÀå Á¡À¯À²À» Â÷ÁöÇß½À´Ï´Ù. µ¥ÀÌÅÍ ¼Òºñ°¡ ±ÞÁõÇϰí 5G ¹× IoT¿Í °°Àº »õ·Î¿î ±â¼úÀÌ È®»êµÊ¿¡ µû¶ó Åë½Å »ç¾÷ÀÚµéÀº Áö¿ª Àüü¿¡¼­ ³×Æ®¿öÅ©ÀÇ È¿À²¼º°ú ¼º´ÉÀ» Çâ»ó½ÃÄÑ¾ß ÇÒ Çʿ伺ÀÌ ´ëµÎµÇ°í ÀÖ½À´Ï´Ù. ³×Æ®¿öÅ© ÃÖÀûÈ­´Â ¹æ´ëÇÑ ¾çÀÇ µ¥ÀÌÅ͸¦ ºÐ¼®ÇÏ¿© ´ë¿ªÆø ÇÒ´çÀ» °³¼±Çϰí, Áö¿¬À» ÁÙÀ̸ç, ²÷±è ¾ø´Â ¿¬°á¼ºÀ» º¸ÀåÇÏ´Â °ÍÀ» Æ÷ÇÔÇÕ´Ï´Ù. ÀÌ ÇÁ·Î¼¼½º´Â ´õ ¸¹Àº µ¥ÀÌÅÍ Æ®·¡ÇÈÀ» ó¸®Çϰí, ¿î¿µ ºñ¿ëÀ» ÃÖ¼ÒÈ­Çϸç, ´õ ³ªÀº »ç¿ëÀÚ °æÇèÀ» Á¦°øÇϰíÀÚ ÇÏ´Â Áö¿ªÀû ¿ä±¸¿¡ ÀÇÇØ ÃßÁøµÇ°í ÀÖ½À´Ï´Ù. Åë½Å »ç¾÷ÀÚ°¡ ³×Æ®¿öÅ© ¼ö¿ä¸¦ ¿¹ÃøÇϰí, ÀáÀçÀûÀÎ ¹®Á¦¸¦ »çÀü¿¡ ÆÄ¾ÇÇÏ¿© ÇØ°áÇϰí, Áö¿ª Àüü¿¡ °ÉÃÄ Àü·«ÀûÀÎ ¾÷±×·¹À̵带 ¼öÇàÇÒ ¼ö ÀÖµµ·Ï Åë½Å ¾Ö³Î¸®Æ½½º ÅøÀÌ ¸Å¿ì Áß¿äÇØÁö°í ÀÖ½À´Ï´Ù.

CAGRÀÌ °¡Àå ³ôÀº Áö¿ª :

À¯·´Àº ¿¹Ãø ±â°£ Áß ¼öÀͼº ³ôÀº ¼ºÀåÀ» ÀÌ·ê °ÍÀ¸·Î ¿¹»óµË´Ï´Ù. À¯·´ Åë½Å ºÎ¹®¿¡¼­´Â Åõ¸í¼º, °æÀï, Çõ½ÅÀ» ÃËÁøÇÏ´Â Á¤ºÎ ±ÔÁ¦°¡ Åë½Å ¾Ö³Î¸®Æ½½ºÀÇ È¯°æÀ» Å©°Ô °­È­Çϰí ÀÖ½À´Ï´Ù. ÀÏ¹Ý µ¥ÀÌÅÍ º¸È£ ±ÔÁ¤(GDPR(EU °³ÀÎÁ¤º¸º¸È£±ÔÁ¤))°ú °°Àº ±ÔÁ¦´Â Åë½Å »ç¾÷ÀÚ°¡ µ¥ÀÌÅ͸¦ Ã¥ÀÓ°¨ ÀÖ°Ô Ãë±ÞÇϵµ·Ï º¸ÀåÇϰí, ¼ÒºñÀÚÀÇ ½Å·Ú¸¦ Çâ»ó½Ã۸ç, Áö¿ª Àüü¿¡¼­ º¸´Ù Á¾ÇÕÀûÀÎ µ¥ÀÌÅÍ ¼öÁý ¹× ºÐ¼®À» ÃËÁøÇϰí ÀÖ½À´Ï´Ù. ·Î¹Ö ¿ä±Ý ÆóÁö, ³×Æ®¿öÅ© ÀÎÇÁ¶ó °³¼± ÃËÁø µî °æÀïÀ» ÃËÁøÇϱâ À§ÇÑ À¯·´ À§¿øÈ¸ÀÇ ±¸»óÀº Åë½Å »ç¾÷ÀÚµéÀÌ °æÀï·ÂÀ» À¯ÁöÇÏ°í ¼­ºñ½º¸¦ ÃÖÀûÈ­Çϱâ À§ÇØ °í±Þ ºÐ¼®À» µµÀÔÇϵµ·Ï Àå·ÁÇϰí ÀÖ½À´Ï´Ù.

¹«·á ¸ÂÃãÇü ¼­ºñ½º :

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

  • ±â¾÷ °³¿ä
    • Ãß°¡ ½ÃÀå ±â¾÷ÀÇ Á¾ÇÕÀûÀÎ ÇÁ·ÎÆÄÀϸµ(ÃÖ´ë 3»ç)
    • ÁÖ¿ä ±â¾÷ÀÇ SWOT ºÐ¼®(ÃÖ´ë 3»ç)
  • Áö¿ª ¼¼ºÐÈ­
    • °í°´ÀÇ °ü½É¿¡ µû¸¥ ÁÖ¿ä ±¹°¡º° ½ÃÀå ÃßÁ¤Ä¡, ¿¹Ãø, CAGR(ÁÖ: Ÿ´ç¼º È®Àο¡ µû¶ó ´Ù¸§)
  • °æÀï»ç º¥Ä¡¸¶Å·
    • Á¦Ç° Æ÷Æ®Æú¸®¿À, Áö¿ªÀû ÀÔÁö, Àü·«Àû Á¦ÈÞ¸¦ ±â¹ÝÀ¸·Î ÇÑ ÁÖ¿ä ±â¾÷ º¥Ä¡¸¶Å·

¸ñÂ÷

Á¦1Àå °³¿ä

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 ¾îÇÁ·ÎÄ¡
  • Á¶»ç Á¤º¸¿ø
    • 1Â÷ Á¶»ç Á¤º¸¿ø
    • 2Â÷ Á¶»ç Á¤º¸¿ø
    • ÀüÁ¦Á¶°Ç

Á¦3Àå ½ÃÀå µ¿Ç⠺м®

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

Á¦4Àå Porter's Five Forces ºÐ¼®

  • °ø±Þ ±â¾÷ÀÇ ±³¼··Â
  • ¹ÙÀ̾îÀÇ ±³¼··Â
  • ´ëüǰÀÇ À§Çù
  • ½Å±Ô ÁøÃâ¾÷üÀÇ À§Çù
  • °æÀï ±â¾÷ °£ °æÀï °ü°è

Á¦5Àå ¼¼°èÀÇ Åë½Å ¾Ö³Î¸®Æ½½º ½ÃÀå : ÄÄÆ÷³ÍÆ®º°

  • ¼ÒÇÁÆ®¿þ¾î
  • Çϵå¿þ¾î
  • ¼­ºñ½º
    • ¸Å´ÏÁöµå ¼­ºñ½º
    • Àü¹® ¼­ºñ½º

Á¦6Àå ¼¼°èÀÇ Åë½Å ¾Ö³Î¸®Æ½½º ½ÃÀå : µµÀÔº°

  • Ŭ¶ó¿ìµå
  • ¿ÂÇÁ·¹¹Ì½º

Á¦7Àå ¼¼°èÀÇ Åë½Å ¾Ö³Î¸®Æ½½º ½ÃÀå : ±â¾÷ ±Ô¸ðº°

  • Áß¼Ò±â¾÷
  • ´ë±â¾÷

Á¦8Àå ¼¼°èÀÇ Åë½Å ¾Ö³Î¸®Æ½½º ½ÃÀå : ¿ëµµº°

  • ¼­ºñ½º ºÐ¼®
  • ³×Æ®¿öÅ© ºÐ¼®
  • °í°´ ºÐ¼®
  • ¼¼ÀÏÁî ¹× ¸¶ÄÉÆÃ °ü¸®
  • ¸®½ºÅ©¿Í ÄÄÇöóÀ̾𽺠°ü¸®
  • ÀÎÀç °ü¸®
  • ±âŸ ¿ëµµ

Á¦9Àå ¼¼°èÀÇ Åë½Å ¾Ö³Î¸®Æ½½º ½ÃÀå : ÃÖÁ¾»ç¿ëÀÚº°

  • ¹Ìµð¾î¿Í ¿£ÅÍÅ×ÀÎ¸ÕÆ®
  • ¿î¼Û¡¤¹°·ù
  • ¼Ò¸Å¡¤E-Commerce
  • Á¤ºÎ
  • ¹Ìµð¾î¿Í ¿£ÅÍÅ×ÀÎ¸ÕÆ®
  • ±âŸ ÃÖÁ¾»ç¿ëÀÚ

Á¦10Àå ¼¼°èÀÇ Åë½Å ¾Ö³Î¸®Æ½½º ½ÃÀå : Áö¿ªº°

  • 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¦11Àå ÁÖ¿ä ¹ßÀü

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

Á¦12Àå ±â¾÷ ÇÁ·ÎÆÄÀϸµ

  • SAP SE
  • Accenture Plc
  • Adobe Inc
  • Cisco Systems Inc
  • Huawei Technologies
  • International Business Machines Corporation
  • Microsoft Corporation
  • Oracle Corporation
  • Teradata Corporation
  • Vodafone Group
KSA 24.08.23

According to Stratistics MRC, the Global Telecom Analytics Market is accounted for $7.8 billion in 2024 and is expected to reach $19.4 billion by 2030 growing at a CAGR of 16.5% during the forecast period. Telecom analytics refers to the process of gathering, interpreting, and applying data from telecommunications networks and systems to optimize operations and enhance service delivery. It involves analyzing vast amounts of data generated from call records, network performance metrics, customer interactions, and more, using advanced analytical techniques and tools. By extracting actionable insights, telecom analytics helps companies improve network efficiency, predict and prevent service disruptions, understand customer behavior for targeted marketing, and optimize resource allocation.

According to the research study by Statista, Global Consumer Survey conducted in the United States in 2022, it has been found that 44 percent of respondents use online storage for files and pictures, while 40 percent of respondents use online applications to create office documents.

Market Dynamics:

Driver:

Increasing demand for subscriber insights

The increasing demand for subscriber insights in Telecom Analytics reflects a growing recognition of data-driven decision-making in the telecommunications industry. Telecom companies are leveraging advanced analytics to gain deeper understanding of subscriber behavior, preferences, and trends. By analyzing vast amounts of data generated from customer interactions, service usage, and network performance, these insights enable providers to personalize offerings, optimize network resources, and improve overall customer experience.

Restraint:

Data privacy and security concerns

Data privacy and security concerns significantly impact telecom analytics by restricting access to valuable customer information and hindering data-driven insights. Telecom companies rely heavily on analyzing vast amounts of customer data to optimize services, predict trends, and enhance user experiences. However, stringent data protection regulations, such as GDPR and CCPA, necessitate rigorous data handling and storage practices to prevent breaches and misuse. This compliance often involves complex encryption methods and restricted data access, which can limit the breadth of analytics and slow down decision-making processes.

Opportunity:

Rising demand for predictive analytics

The increasing demand for predictive analytics in the telecom industry is transforming how companies operate and serve their customers. Predictive analytics utilizes data mining, machine learning, and statistical algorithms to analyze historical data and make predictions about future events or behaviors. In telecom, this translates to more personalized customer experiences, improved network management, and enhanced operational efficiency. By analyzing customer behavior patterns, telecom companies can anticipate churn, tailor marketing strategies, and offer targeted promotions, thereby increasing customer satisfaction and loyalty.

Threat:

Complexity of data integration

Data integration in telecom analytics is complex due to the vast and varied nature of the data sources involved. Telecom operators manage an extensive array of data types, including customer interactions, network performance metrics, billing information, and service usage patterns. These data sources are often stored in disparate systems with different formats, structures, and standards. Integrating this data requires significant effort to ensure consistency, accuracy, and timeliness. However, the challenge is further compounded by the need to merge historical data with real-time inputs, address data quality issues, and maintain privacy and security standards.

Covid-19 Impact:

The COVID-19 pandemic significantly impacted telecom analytics by accelerating digital transformation and altering usage patterns. With widespread lockdowns and remote work becoming the norm, there was a sharp increase in internet and mobile data consumption, prompting telecom companies to reevaluate their network capacities and service offerings. Analytics became crucial in managing this surge, helping providers optimize network performance, predict traffic spikes, and enhance customer experience. The pandemic exposed disparities in digital access, leading to a heightened focus on bridging connectivity gaps.

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

Hardware segment is expected to be the largest during the forecast period by integrating cutting-edge technologies and high-performance components into network infrastructure. Modern telecom analytics relies heavily on real-time data processing and analysis, which requires robust hardware solutions capable of handling vast amounts of data with low latency. Enhanced servers, specialized processors, and high-capacity storage systems are crucial in managing and interpreting complex network data streams. These advancements enable telecom providers to implement sophisticated analytics algorithms that improve network performance, optimize resource allocation, and enhance customer experience.

The Network Analytics segment is expected to have the highest CAGR during the forecast period

Network Analytics segment is expected to have the highest CAGR during the forecast period. Network Analytics is revolutionizing Telecom Analytics by providing deeper insights into network performance and customer behavior. This enhancement involves using advanced data analysis and machine learning to monitor and optimize network operations in real-time. By analyzing vast amounts of network data, Telecom Analytics can identify patterns, predict potential issues, and improve decision-making. Furthermore, this leads to more efficient network management, reduced downtime, and enhanced service quality for users. For telecom operators, Network Analytics enables proactive maintenance, better resource allocation, and targeted improvements, all of which contribute to a superior customer experience.

Region with largest share:

North America region commanded the largest share of the market over the projection period. As data consumption surges and new technologies like 5G and IoT proliferate, telecom operators face increasing pressure to enhance network efficiency and performance across the region. Network optimization involves analyzing vast amounts of data to improve bandwidth allocation, reduce latency, and ensure seamless connectivity. This process is driven by the regional need to handle higher data traffic, minimize operational costs, and provide a superior user experience. Telecom analytics tools have become crucial, enabling operators to predict network demand, identify and address potential issues proactively and implement strategic upgrades across the region.

Region with highest CAGR:

Europe region is projected to witness profitable growth during the extrapolated period. In the European telecom sector, government regulations are substantially enhancing the landscape of telecom analytics by fostering transparency, competition, and innovation. Regulations such as the General Data Protection Regulation (GDPR) ensure that telecom operators handle data responsibly, which improves consumer trust and encourages more comprehensive data collection and analysis across the region. The European Commission's initiatives to promote competition, like the removal of roaming charges and the push for better network infrastructure, drive telecom companies to adopt advanced analytics to stay competitive and optimize their services.

Key players in the market

Some of the key players in Telecom Analytics market include SAP SE, Accenture Plc, Adobe Inc, Cisco Systems Inc, Huawei Technologies, International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, Teradata Corporation and Vodafone Group.

Key Developments:

In April 2024, Vodafone Idea (Vi) has initiated a fund infusion plan, starting with a preferential share issue to raise Rs 2,075 Crore from an Aditya Birla Group entity, essential for its financial revitalization.

In February 2024, Deutsche Telekom, Singtel, e& Group, SoftBank, and SK Telecom officially launched the Global Telco AI Alliance (GTAA) at MWC Barcelona 2024. Moreover, during the launch event, the telcos further announced plans to establish a joint venture, via which the companies will focus on developing Large Language Models (LLMs) specifically tailored to the needs of telecommunications companies.

In May 2023, Microsoft announced a new partnership with Orange to help Orange improve its network analytics capabilities. The partnership will use Microsoft's Azure cloud platform and Azure Machine Learning to help Orange analyze its network data and identify opportunities to improve performance and customer experience.

In February 2023, Google Cloud announced a partnership with Ericsson to help telecom operators improve their network performance and customer experience. The partnership will focus on using Google Cloud's analytics and machine learning capabilities to help Ericsson's customers gain insights into their network data.

In February 2023, Nokia Corporation announces the launch of AVA Customer and Mobile Network Insights, a cloud-native analytics software solution that simplifies 5G network data collection and analysis and delivers powerful, most cost-effective analytics to communications service providers (CSPs). With the help of machine learning and AI tools, the solution help to support automated and intelligent solution decision-making based on correlated reports generated from data across 5G networks.

Components Covered:

  • Software
  • Hardware
  • Services

Deployments Covered:

  • Cloud
  • On-premises

Enterprise Sizes Covered:

  • Small and Medium-sized Enterprises
  • Large Enterprises

Applications Covered:

  • Service Analytics
  • Network Analytics
  • Customer Analytics
  • Sales and Marketing Management
  • Risk and Compliance Management
  • Workforce Management
  • Other Applications

End Users Covered:

  • Media & Entertainment
  • Transportation & Logistics
  • Retail & E-Commerce
  • Government
  • Media & Entertainment
  • 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 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 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 Telecom Analytics Market, By Component

  • 5.1 Introduction
  • 5.2 Software
  • 5.3 Hardware
  • 5.4 Services
    • 5.4.1 Managed Services
    • 5.4.2 Professional Services

6 Global Telecom Analytics Market, By Deployment

  • 6.1 Introduction
  • 6.2 Cloud
  • 6.3 On-premises

7 Global Telecom Analytics Market, By Enterprise Size

  • 7.1 Introduction
  • 7.2 Small & Medium-sized Enterprises
  • 7.3 Large Enterprises

8 Global Telecom Analytics Market, By Application

  • 8.1 Introduction
  • 8.2 Service Analytics
  • 8.3 Network Analytics
  • 8.4 Customer Analytics
  • 8.5 Sales and Marketing Management
  • 8.6 Risk and Compliance Management
  • 8.7 Workforce Management
  • 8.8 Other Applications

9 Global Telecom Analytics Market, By End User

  • 9.1 Introduction
  • 9.2 Media & Entertainment
  • 9.3 Transportation & Logistics
  • 9.4 Retail & E-Commerce
  • 9.5 Government
  • 9.6 Media & Entertainment
  • 9.7 Other End Users

10 Global Telecom Analytics Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 SAP SE
  • 12.2 Accenture Plc
  • 12.3 Adobe Inc
  • 12.4 Cisco Systems Inc
  • 12.5 Huawei Technologies
  • 12.6 International Business Machines Corporation
  • 12.7 Microsoft Corporation
  • 12.8 Oracle Corporation
  • 12.9 Teradata Corporation
  • 12.10 Vodafone Group
ºñ±³¸®½ºÆ®
0 °ÇÀÇ »óǰÀ» ¼±Åà Áß
»óǰ ºñ±³Çϱâ
Àüü»èÁ¦