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Halo Sobat Teknokrat – Penyerapan data adalah proses memperoleh dan memasukkan data ke dalam gudang data. Temukan lebih lanjut tentang penyerapan data sekarang.
Sederhananya, penyerapan data adalah proses memindahkan atau mereplikasi data dari sumber dan memindahkannya ke tujuan baru. Beberapa sumber dari mana data dipindahkan atau direplikasi adalah database, file, atau bahkan aliran data IoT. Data yang dipindahkan dan/atau direplikasi selama penyerapan data kemudian disimpan di tujuan yang dapat berada di lokasi. Namun, lebih sering daripada tidak, itu ada di cloud.
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Data yang diserap tetap dalam bentuk mentah dan aslinya, seperti yang ada di sumbernya, jadi jika ada kebutuhan untuk mengurai atau mengubah data menjadi format yang lebih kompatibel dengan analitik atau aplikasi lain, itu adalah operasi transformasi lanjutan yang masih akan perlu dilakukan. Dalam panduan ini, kita akan membahas spesifikasi dan manfaat tambahan dari penyerapan data, serta beberapa alat penyerapan data teratas yang perlu dipertimbangkan untuk diinvestasikan.
Daftar Isi
Apa tujuan dari penyerapan data?
Tujuan dari penyerapan data adalah untuk memindahkan volume data yang besar dengan cepat. Ini dimungkinkan karena tidak perlu mengubah data selama pemindahan atau replikasi data. Kecepatan konsumsi memungkinkan organisasi untuk memindahkan data dengan cepat.
Penyerapan data menggunakan otomatisasi perangkat lunak untuk memindahkan data dalam jumlah besar secara efisien, karena pengoperasiannya memerlukan sedikit upaya manual dari TI. Penyerapan data adalah sarana massal pengambilan data dari hampir semua sumber. Itu dapat menangani volume data yang sangat besar yang memasuki jaringan perusahaan setiap hari.
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Penyerapan data adalah teknologi “penggerak” yang dapat digabungkan dengan teknologi pengeditan dan pemformatan data seperti ETL. Dengan sendirinya, penyerapan data hanya menelan data; itu tidak mengubahnya.
Bagi banyak organisasi, penyerapan data adalah alat penting yang membantu mereka mengelola ujung depan data dan data yang baru saja masuk ke perusahaan mereka. Alat penyerapan data memungkinkan perusahaan untuk segera memindahkan data mereka ke tempat penyimpanan data pusat tanpa risiko meninggalkan data berharga “di luar sana” di sumber yang nantinya tidak dapat diakses lagi.
Jenis penyerapan data
Ada tiga tipe dasar penyerapan data: waktu nyata, batch, dan lambda.
Penyerapan data waktu nyata
Penyerapan data real-time segera memindahkan data saat masuk dari sistem sumber seperti IoT, file, dan database.
Untuk menghemat pergerakan data ini, penyerapan data menggunakan metode pengambilan data yang sudah terbukti benar: Metode ini hanya menangkap data yang telah diubah sejak terakhir kali data dikumpulkan. Operasi ini dikenal sebagai “mengubah pengambilan data”.
Penyerapan data waktu nyata sering digunakan untuk memindahkan data aplikasi yang terkait dengan perdagangan saham atau pemantauan infrastruktur IoT.
Penyerapan data batch
Penyerapan data batch melibatkan penyerapan data pada malam hari (dalam kumpulan data) atau pada interval pengumpulan data berkala yang dijadwalkan pada siang hari. Hal ini memungkinkan organisasi untuk menangkap semua data yang mereka butuhkan untuk pengambilan keputusan secara tepat waktu pada tingkat yang tidak memerlukan pengambilan data secara real-time.
Mengumpulkan data penjualan secara berkala dari gerai penjualan ritel dan e-niaga terdistribusi adalah contoh yang baik tentang kapan penyerapan batch berkala akan digunakan.
Penyerapan data Lambda
Penyerapan data Lambda menggabungkan praktik penyerapan data real-time dan batch. Tujuannya adalah untuk memindahkan data secepat mungkin.
Jika ada masalah latensi atau kecepatan transfer data yang dapat memengaruhi kinerja, model teknik penyerapan data lambda dapat mengantri data untuk sementara, mengirimkannya ke repositori data target hanya jika repositori tersebut tersedia.
Penyerapan data vs. ETL
Penyerapan data adalah proses tindakan cepat yang mengambil data mentah dari file sumber dan memindahkan data secara langsung, apa adanya ke repositori data pusat target.
ETL juga merupakan alat transfer data, tetapi lebih lambat daripada penyerapan data karena ETL juga mengubah data menjadi format yang sesuai untuk diakses di pusat penyimpanan data tempat data akan disimpan.
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Keuntungan dari penyerapan data adalah Anda dapat langsung menangkap semua data yang masuk. Namun, setelah Anda memiliki datanya, Anda masih harus mengerjakannya agar dapat diformat untuk digunakan.
Dengan ETL, sebagian besar pemformatan data sudah selesai. Kelemahan ETL adalah membutuhkan waktu lebih lama untuk menangkap dan memproses data yang masuk.
Alat penyerapan data teratas
Tepat Terhubung

Sebelumnya dikenal sebagai Syncsort, Tepat Terhubung menyediakan penyerapan data real-time dan batch untuk analitik lanjutan, migrasi data, dan sasaran pembelajaran mesin. Ini juga mendukung fungsionalitas CDC dan ETL.
Precisely Connect dapat mencari dan menargetkan data ke sistem lokal atau berbasis cloud. Data dapat dalam format basis data relasional, data besar, streaming atau mainframe.
Apache Kafka

Ditujukan untuk konsumsi data besar, Apache Kafka adalah solusi perangkat lunak open source yang menyediakan integrasi data throughput tinggi, analitik streaming, dan pipeline data. Itu dapat terhubung ke berbagai sumber data eksternal. Itu juga merupakan pintu gerbang ke sejumlah besar alat tambahan dan fungsionalitas dari komunitas sumber terbuka global.
Kain Data Talend

Kain Data Talend memungkinkan Anda menarik data dari sebanyak 1.000 sumber data yang berbeda. Data dapat ditargetkan ke repositori data internal atau berbasis cloud.
Layanan cloud yang didukung Talend adalah Google Cloud Platform, Amazon Web Services, Snowflake, Microsoft Azure, dan Databricks. Talend Data Fabric juga memiliki fitur deteksi dan koreksi kesalahan otomatis.
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