Di zaman transformasi digital seperti sekarang, profesi data scientis dan data analyst sangat digemari oleh banyak job seeker. Kedua profesi ini memiliki keterkaitan yang sangat erat dengan pengolahan data. Kalau begitu, apa saja perbedaan data scientis dan data analyst?
Ketahui Perbedaan Data Scientis dan Data Analyst
Sangat berhubungan erat dengan data, namun melihat fakta profesi tersebut justru memiliki deskripsi yang sangat berbeda.
Bahkan, kedua profesi tersebut memegang peran dan tanggung jawab yang tidak sama. Jadi sebelum memutuskan terjun menjadi Data Scientis atau Data Analyst pastikan sudah memahami seluk beluknya.
Berdasarkan Deskripsi Pekerjaan
Berdasarkan deskripsi pekerjaan perbedaan data scientis dan data analyst bisa terjabarkan sebagai berikut.
- Data Scientis
Seorang yang bekerja sebagai Data Scientis akan banyak melakukan analisa dan menafsirkan sebuah kumpulan data yang sifatnya kompleks.
Berdasarkan karakteristiknya, memiliki kapasitas untuk mengungkap sebuah tren memakai data. Didukung kemampuan pemrograman untuk mengubah data yang semula berbahasa program menjadi dimengerti orang awam.
Untuk itu Data Scientis ini adalah orang yang juga ahli dalam membaca coding dan mathematical modeling.
Data yang sudah ada harus di match dengan tujuan perusahaan, supaya mendapat solusi kemudian membuat eksperimennya. Lalu data akan terbagikan kepada tim atau perusahaan dalam format sederhana.
- Data Analyst
Seorang Data Analyst akan melakukan analisa data untuk menghasilkan sebuah laporan yang menjadi intisari kinerja perusahaan.
Data Analyst akan berhadapan dengan berbagai macam data. Serupa tapi tak sama, membuat Data Analyst ini kerap disebut sebagai junior Data Scientis.
Jadi dalam tahapan pekerjaannya, Data Analyst akan mengolah data, menarik sebuah kesimpulan dan mengubahnya ke dalam visualisasi.
Oleh karenanya, seorang data analyst harus bisa mencari insight baru dari sebuah data yang teranalisa. Tujuannya adalah untuk memajukan bisnis perusahaan dari berbagai aspek
Berdasarkan Skill yang Dibutuhkan
Berdasarkan deskripsi skill yang dibutuhkan data scientis dan data analyst bisa terjabarkan sebagai berikut.
Data Scientis
- Paham baik dengan machine learning dan algorita. Misalnya k-NN, Naive Bayes, SVM, Decision Forests dan lain sebagainya.
- Paham menggunakan toolkit seperti R, Weka, NumPy, MatLab, dan lain sebagainya.
- Mahir mengoperasikan database seperti SQL, Hive, dan juga Pig.
- Fasih memakai NoSQL database misalnya saja MongoDB, Cassandra, Hbase.
- Ahli dalam statistik mulai dari distribusi, pengujian, regresi, dan proses lainnya.
- Terampil dalam scripting dan programming.
- Berorientasi pada data.
- Memahami pengetahuan bisnis.
- Mampu menjadi leadership dan bekerja tim.
Data Analyst
- Mahir dalam mengolah data.
- Tingkat analisa yang baik dan detail.
- Memiliki kemampuan statisik dan matematis yang mumpuni.
- Mampu berpikir secara kritis.
- Teliti dan jeli terhadap data yang terproses.
- Komunikasi dan bahasa yang baik secara lisan maupun tulisan.
Terlepas dari perbedaan kedua profesi tersebut, keduanya tetap memiliki persamaan :
Keduanya harus terbiasa mengoperasikan perangkat lunak pengolah data. Sebut saja seperti My SQL, Cassandra, atau Hadoop. Semakin baik tingkat pengoperasian perangkat lunak, maka kinerja lebih baik.
Persamaan lainnya dari Data Scinetis dan Data Analyst adalah pandai memahami bahasa program. Hal ini sangat vital untuk keduanya, karena pola kerja yang menuntut penggalian informasi.
Semakin banyak dan mendetail informasi yang sudah tergali, akan menjadi lebih baik bagi penetapan rencana strategis perusahaan.
Sekarang jadi sudah lebih paham ya mengenai perbedaan antara keduanya, khususnya dalam pola kerja.
Meski sebenarnya kedua profesi tersebut juga memiliki persamaan yang tidak berbeda jauh. Keahlian dalam olah data dan bahasa program yang dapat menunjang kedua profesi tersebut.
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