Changes
On March 30, 2023 at 1:30:38 PM UTC, CleverMaps Data Catalog:
-
Changed value of field
task_created
of resource Consumer Spending by Product Groups to2023-03-16 10:54:14.637554
(previously2023-02-17 17:10:46.522845
) in Consumer Spending by Product Groups – France (Communes)
f | 1 | { | f | 1 | { |
2 | "author": "Franti\u0161ek Pavl\u00ed\u010dek", | 2 | "author": "Franti\u0161ek Pavl\u00ed\u010dek", | ||
3 | "author_email": "frantisek.pavlicek@clevermaps.io", | 3 | "author_email": "frantisek.pavlicek@clevermaps.io", | ||
4 | "availability": "Upon request", | 4 | "availability": "Upon request", | ||
5 | "category": "Geotypes/Consumer Segments", | 5 | "category": "Geotypes/Consumer Segments", | ||
6 | "coverage": "France", | 6 | "coverage": "France", | ||
7 | "creator_user_id": "e2185bb8-8a2a-457e-a273-2e757a7866d8", | 7 | "creator_user_id": "e2185bb8-8a2a-457e-a273-2e757a7866d8", | ||
8 | "crs": "No coordinate system", | 8 | "crs": "No coordinate system", | ||
9 | "data_source": "https://www.mb-research.de/", | 9 | "data_source": "https://www.mb-research.de/", | ||
10 | "dataset_dimension": "Dataset", | 10 | "dataset_dimension": "Dataset", | ||
11 | "date_validity": "2021-01-01", | 11 | "date_validity": "2021-01-01", | ||
12 | "dimension": | 12 | "dimension": | ||
13 | "https://secure.clevermaps.io/#/projectList/project/m30b90q331i3gio3", | 13 | "https://secure.clevermaps.io/#/projectList/project/m30b90q331i3gio3", | ||
14 | "for_sale": "For sale", | 14 | "for_sale": "For sale", | ||
15 | "geometry": "No geometry", | 15 | "geometry": "No geometry", | ||
16 | "groups": [], | 16 | "groups": [], | ||
17 | "id": "d0779c1f-863e-4911-8dd6-0f8d7fe07a44", | 17 | "id": "d0779c1f-863e-4911-8dd6-0f8d7fe07a44", | ||
18 | "isopen": true, | 18 | "isopen": true, | ||
19 | "license_id": "cc-zero", | 19 | "license_id": "cc-zero", | ||
20 | "license_title": "Creative Commons CCZero", | 20 | "license_title": "Creative Commons CCZero", | ||
21 | "license_url": "http://www.opendefinition.org/licenses/cc-zero", | 21 | "license_url": "http://www.opendefinition.org/licenses/cc-zero", | ||
22 | "lowest_granularity": "Municipality", | 22 | "lowest_granularity": "Municipality", | ||
23 | "maintainer": null, | 23 | "maintainer": null, | ||
24 | "maintainer_email": null, | 24 | "maintainer_email": null, | ||
25 | "metadata_created": "2023-03-01T13:30:53.940623", | 25 | "metadata_created": "2023-03-01T13:30:53.940623", | ||
n | 26 | "metadata_modified": "2023-03-01T13:30:53.940630", | n | 26 | "metadata_modified": "2023-03-30T13:30:38.232342", |
27 | "name": | 27 | "name": | ||
28 | mb-research-consumer_spending_by_product_groups_-_france_mb-research", | 28 | mb-research-consumer_spending_by_product_groups_-_france_mb-research", | ||
29 | "notes": "This dataset contains information about the kind od | 29 | "notes": "This dataset contains information about the kind od | ||
30 | products that customers tend to spend for the most. You can purchase | 30 | products that customers tend to spend for the most. You can purchase | ||
31 | the dataset on the level of communes (35 270 units). This sort of | 31 | the dataset on the level of communes (35 270 units). This sort of | ||
32 | dataset is also available in other European countries.", | 32 | dataset is also available in other European countries.", | ||
33 | "num_resources": 1, | 33 | "num_resources": 1, | ||
34 | "num_tags": 5, | 34 | "num_tags": 5, | ||
35 | "organization": { | 35 | "organization": { | ||
36 | "approval_status": "approved", | 36 | "approval_status": "approved", | ||
37 | "created": "2023-01-29T16:55:22.474138", | 37 | "created": "2023-01-29T16:55:22.474138", | ||
38 | "description": "MB-Research is a company specializing itself in | 38 | "description": "MB-Research is a company specializing itself in | ||
39 | providing its users with economic data on different administrative and | 39 | providing its users with economic data on different administrative and | ||
40 | postal levels across Europe. The company mostly offers data about | 40 | postal levels across Europe. The company mostly offers data about | ||
41 | purchasing power, unemployment, demography and also series of | 41 | purchasing power, unemployment, demography and also series of | ||
42 | different packages derived from this data.", | 42 | different packages derived from this data.", | ||
43 | "id": "bea8ce14-5031-4087-ac7f-1e30b4395fbd", | 43 | "id": "bea8ce14-5031-4087-ac7f-1e30b4395fbd", | ||
44 | "image_url": | 44 | "image_url": | ||
45 | bs.twimg.com/profile_images/1275751395032006656/nQgmFA8I_400x400.jpg", | 45 | bs.twimg.com/profile_images/1275751395032006656/nQgmFA8I_400x400.jpg", | ||
46 | "is_organization": true, | 46 | "is_organization": true, | ||
47 | "name": "mb-research", | 47 | "name": "mb-research", | ||
48 | "state": "active", | 48 | "state": "active", | ||
49 | "title": "MB-Research", | 49 | "title": "MB-Research", | ||
50 | "type": "organization" | 50 | "type": "organization" | ||
51 | }, | 51 | }, | ||
52 | "owner_org": "bea8ce14-5031-4087-ac7f-1e30b4395fbd", | 52 | "owner_org": "bea8ce14-5031-4087-ac7f-1e30b4395fbd", | ||
53 | "price_dataset_one_time": "117500", | 53 | "price_dataset_one_time": "117500", | ||
54 | "price_notes": "For all product groups. Also available for one | 54 | "price_notes": "For all product groups. Also available for one | ||
55 | product group for 2150 \u20ac, each additional product group is 650 | 55 | product group for 2150 \u20ac, each additional product group is 650 | ||
56 | \u20ac. Please find the relevant documents for price creation here: | 56 | \u20ac. Please find the relevant documents for price creation here: | ||
57 | s://drive.google.com/drive/folders/18yCEyUhl-_0-tzXQ5uxMRCOx56B4dHTp", | 57 | s://drive.google.com/drive/folders/18yCEyUhl-_0-tzXQ5uxMRCOx56B4dHTp", | ||
58 | "private": false, | 58 | "private": false, | ||
59 | "relationships_as_object": [], | 59 | "relationships_as_object": [], | ||
60 | "relationships_as_subject": [], | 60 | "relationships_as_subject": [], | ||
61 | "resources": [ | 61 | "resources": [ | ||
62 | { | 62 | { | ||
63 | "cache_last_updated": null, | 63 | "cache_last_updated": null, | ||
64 | "cache_url": null, | 64 | "cache_url": null, | ||
65 | "ckan_url": "https://datacatalog.ps.cleveranalytics.com", | 65 | "ckan_url": "https://datacatalog.ps.cleveranalytics.com", | ||
66 | "created": "2022-06-10T06:55:18.551176", | 66 | "created": "2022-06-10T06:55:18.551176", | ||
67 | "datastore_active": true, | 67 | "datastore_active": true, | ||
68 | "datastore_contains_all_records_of_source_file": false, | 68 | "datastore_contains_all_records_of_source_file": false, | ||
69 | "description": "Data sample", | 69 | "description": "Data sample", | ||
70 | "format": "CSV", | 70 | "format": "CSV", | ||
71 | "hash": "11e707d829d96462ca4a9a3320617178", | 71 | "hash": "11e707d829d96462ca4a9a3320617178", | ||
72 | "id": "b4883dca-bed9-41f3-88c6-e732d9e71f0b", | 72 | "id": "b4883dca-bed9-41f3-88c6-e732d9e71f0b", | ||
73 | "ignore_hash": true, | 73 | "ignore_hash": true, | ||
74 | "last_modified": null, | 74 | "last_modified": null, | ||
75 | "map": | 75 | "map": | ||
76 | nsumer_spending_view?token=he2w0Y3gnLF1hFKufYiw1xqUv7ZKNvidPFaMOwyr2e0 | 76 | nsumer_spending_view?token=he2w0Y3gnLF1hFKufYiw1xqUv7ZKNvidPFaMOwyr2e0 | ||
77 | ", | 77 | ", | ||
n | 78 | "metadata_modified": "2023-03-01T13:30:53.931723", | n | 78 | "metadata_modified": "2023-03-30T13:30:38.235867", |
79 | "mimetype": null, | 79 | "mimetype": null, | ||
80 | "mimetype_inner": null, | 80 | "mimetype_inner": null, | ||
81 | "name": "Consumer Spending by Product Groups", | 81 | "name": "Consumer Spending by Product Groups", | ||
82 | "original_url": | 82 | "original_url": | ||
83 | 3/data_partners/mb_research/mb_research_sample_consumer_spending.csv", | 83 | 3/data_partners/mb_research/mb_research_sample_consumer_spending.csv", | ||
84 | "package_id": "d0779c1f-863e-4911-8dd6-0f8d7fe07a44", | 84 | "package_id": "d0779c1f-863e-4911-8dd6-0f8d7fe07a44", | ||
85 | "position": 0, | 85 | "position": 0, | ||
86 | "resource_id": "b4883dca-bed9-41f3-88c6-e732d9e71f0b", | 86 | "resource_id": "b4883dca-bed9-41f3-88c6-e732d9e71f0b", | ||
87 | "resource_type": null, | 87 | "resource_type": null, | ||
88 | "s3link": | 88 | "s3link": | ||
89 | g/data_partners/mb_research/mb_research_sample_consumer_spending.csv", | 89 | g/data_partners/mb_research/mb_research_sample_consumer_spending.csv", | ||
90 | "set_url_type": false, | 90 | "set_url_type": false, | ||
91 | "size": null, | 91 | "size": null, | ||
92 | "state": "active", | 92 | "state": "active", | ||
t | 93 | "task_created": "2023-02-17 17:10:46.522845", | t | 93 | "task_created": "2023-03-16 10:54:14.637554", |
94 | "url": | 94 | "url": | ||
95 | 3/data_partners/mb_research/mb_research_sample_consumer_spending.csv", | 95 | 3/data_partners/mb_research/mb_research_sample_consumer_spending.csv", | ||
96 | "url_type": null | 96 | "url_type": null | ||
97 | } | 97 | } | ||
98 | ], | 98 | ], | ||
99 | "state": "active", | 99 | "state": "active", | ||
100 | "tags": [ | 100 | "tags": [ | ||
101 | { | 101 | { | ||
102 | "display_name": "France", | 102 | "display_name": "France", | ||
103 | "id": "ff441ab8-e40e-4be8-bb8d-aaad0d6ecafc", | 103 | "id": "ff441ab8-e40e-4be8-bb8d-aaad0d6ecafc", | ||
104 | "name": "France", | 104 | "name": "France", | ||
105 | "state": "active", | 105 | "state": "active", | ||
106 | "vocabulary_id": null | 106 | "vocabulary_id": null | ||
107 | }, | 107 | }, | ||
108 | { | 108 | { | ||
109 | "display_name": "MB-Research", | 109 | "display_name": "MB-Research", | ||
110 | "id": "6d777b9b-664b-4660-8e8f-3904192e3e09", | 110 | "id": "6d777b9b-664b-4660-8e8f-3904192e3e09", | ||
111 | "name": "MB-Research", | 111 | "name": "MB-Research", | ||
112 | "state": "active", | 112 | "state": "active", | ||
113 | "vocabulary_id": null | 113 | "vocabulary_id": null | ||
114 | }, | 114 | }, | ||
115 | { | 115 | { | ||
116 | "display_name": "consumer spending", | 116 | "display_name": "consumer spending", | ||
117 | "id": "49b4c136-c590-4847-abd3-6eac683728c8", | 117 | "id": "49b4c136-c590-4847-abd3-6eac683728c8", | ||
118 | "name": "consumer spending", | 118 | "name": "consumer spending", | ||
119 | "state": "active", | 119 | "state": "active", | ||
120 | "vocabulary_id": null | 120 | "vocabulary_id": null | ||
121 | }, | 121 | }, | ||
122 | { | 122 | { | ||
123 | "display_name": "consumers", | 123 | "display_name": "consumers", | ||
124 | "id": "7f3db544-d578-436b-9811-a3b3e4a23dcd", | 124 | "id": "7f3db544-d578-436b-9811-a3b3e4a23dcd", | ||
125 | "name": "consumers", | 125 | "name": "consumers", | ||
126 | "state": "active", | 126 | "state": "active", | ||
127 | "vocabulary_id": null | 127 | "vocabulary_id": null | ||
128 | }, | 128 | }, | ||
129 | { | 129 | { | ||
130 | "display_name": "partner", | 130 | "display_name": "partner", | ||
131 | "id": "59088a3f-832b-421c-9601-aa41a3373508", | 131 | "id": "59088a3f-832b-421c-9601-aa41a3373508", | ||
132 | "name": "partner", | 132 | "name": "partner", | ||
133 | "state": "active", | 133 | "state": "active", | ||
134 | "vocabulary_id": null | 134 | "vocabulary_id": null | ||
135 | } | 135 | } | ||
136 | ], | 136 | ], | ||
137 | "title": "Consumer Spending by Product Groups \u2013 France | 137 | "title": "Consumer Spending by Product Groups \u2013 France | ||
138 | (Communes)", | 138 | (Communes)", | ||
139 | "type": "dataset", | 139 | "type": "dataset", | ||
140 | "url": null, | 140 | "url": null, | ||
141 | "use_cases": | 141 | "use_cases": | ||
142 | telligence-market-research,https://www.clevermaps.io/site-evaluation", | 142 | telligence-market-research,https://www.clevermaps.io/site-evaluation", | ||
143 | "use_cases_description": "Finding out the real catchment areas of | 143 | "use_cases_description": "Finding out the real catchment areas of | ||
144 | your branches and comparing them with driving or walking catchment | 144 | your branches and comparing them with driving or walking catchment | ||
145 | areas can help you optimizing the locations of your branches.,Locate | 145 | areas can help you optimizing the locations of your branches.,Locate | ||
146 | the places with an insufficient coverage based on data about | 146 | the places with an insufficient coverage based on data about | ||
147 | population. Evaluate planned locations and find out straightaway what | 147 | population. Evaluate planned locations and find out straightaway what | ||
148 | amount of people will you cover.,Analyze your current market share on | 148 | amount of people will you cover.,Analyze your current market share on | ||
149 | a spatial level to focus your expansion efforts on the areas with a | 149 | a spatial level to focus your expansion efforts on the areas with a | ||
150 | potential customer base and a beneficial number of | 150 | potential customer base and a beneficial number of | ||
151 | competitors.,Analyze the presence of your competition and include the | 151 | competitors.,Analyze the presence of your competition and include the | ||
152 | findings in the business strategy. Location data will help you to try | 152 | findings in the business strategy. Location data will help you to try | ||
153 | targeting areas with more potential.,Evaluate\u00a0the retail | 153 | targeting areas with more potential.,Evaluate\u00a0the retail | ||
154 | potential of any address and measure its attractiveness within its | 154 | potential of any address and measure its attractiveness within its | ||
155 | natural catchment area.\u00a0Choosing the right place for you business | 155 | natural catchment area.\u00a0Choosing the right place for you business | ||
156 | has never been easier.", | 156 | has never been easier.", | ||
157 | "version": null, | 157 | "version": null, | ||
158 | "visualization": "Polygon" | 158 | "visualization": "Polygon" | ||
159 | } | 159 | } |