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This was my first project in building simple overview dashboard. Using data from single csv table, recategorized, and analyzed using Tableau.
| Column Name | Description | Value | Type |
|---|---|---|---|
| Tanggal | Date of goods in or out | Datetime | DATE |
| In / Out | Status of goods IN or OUT | “IN” and “OUT” | Categorical |
| Nomor GRN (Good Received Note) / GDN (Good Deliveries Note) | Invoice number (airway bill) | “01.00” etc | Categorical |
| Gudang | Inventory warehouses | “G1”, “G2”, “G3”,”G4”, “G5”,”G6”, “G7” | Categorical |
| Dari/Kepada | Name of receiver or sender | Ex: “PMI Provinsi Papua” | Categorical |
| Nama Barang | Type of goods | Ex: “Ventilator..” | Categorical |
| Merk Barang | Brand of goods | Ex “Gajah Tunggal” | Categorical |
| Masuk | Qty of IN goods | Pcs, Pasang, etc | Numerical |
| Keluar | Qty of OUT goods | Pcs, Pasang, etc | Numerical |
| Nilai | Price of the goods per date of IN or OUT | IDR | Numerical |
| Jumlah | Total value times Qty (Nilai x Jumlah) | IDR | Numerical |
| Berat Barang | Weight of the goods | Kg | Numerical |
| Total Berat Barang | Total weight of the goods | Kg | Numerical |
In this section we can monitor each of the warehouses stock movements, IN & OUT value qty. All dynamically changes over time using the time filters
Here we can see the main category of the goods for each, some or all warehouses (using filters). It tracked the total capacity and the balance of it. Thus we can see which warehouse that over capacity or lack of certain goods.
Using the same filter (time and warehouses), we can see the main category and specific product name, values and weight. From this section we can get insight such as what kind of goods that has biggest or smallest value, the heaviest or the lightest products.
This time series analyzed of filtered warehouses for its stock movements IN or OUT, also the balance of stocks through time. We can get insights of what time that has the highest or lowest stock movement time.