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· 5 checks — Internal links, mixed-content guards, Open Graph previews, and structured data rolled into one auditable list.
SCORE
90
GRADE
A
FIX
0
REVIEW
3
PASS
2
INFO
0
Checks
5
2 PASS 3 REVIEW
C
Structured Data
Action
1 JSON-LD block(s) found — some improvements recommended.
REVIEW
1 JSON-LD block(s) found — some improvements recommended.
Critical::
Malformed JSON-LD block #1
JSON parse error: Mismatch type map[string]interface {} with value array "at index 0: mismatched type with value\n\n\t[{\"@context\":\"http://schema.org\"\n\t^...............................\n"

JSON parse error: Mismatch type map[string]interface {} with value array "at index 0: mismatched type with value\n\n\t[{\"@context\":\"http://schema.org\"\n\t^...............................\n"

Why this matters

JSON-LD block fails to parse — Google ignores the entire block, so structured data effectively isn't there.

Learn more ▾

Common causes: trailing comma, single quotes instead of double, unescaped quote in a string value. Validate at https://validator.schema.org/ or Search Console's Rich Results Test.

Source: schema.org / Google Search Central

JSON-LD Blocks

Block 1 : ContactPoint
0 properties Invalid
Invalid JSON: Mismatch type map[string]interface {} with value array "at index 0: mismatched type with value\n\n\t[{\"@context\":\"http://schema.org\"\n\t^...............................\n"
[
  {
    "@context": "http://schema.org",
    "@type": "ContactPoint",
    "telephone": "+1-866-330-0121",
    "availableLanguage": "en-US",
    "contactOption": "TollFree",
    "contactType": "Contact",
    "name": "Databricks Contact",
    "@id": "https://www.databricks.com/#ContactPoint"
  },
  {
    "@context": "http://schema.org",
    "@type": "Organization",
    "description": "The Databricks Platform is the world\u2019s first data intelligence platform powered by generative AI. Infuse AI into every facet of your business.",
    "name": "Databricks",
    "disambiguatingDescription": "Your data. Your AI. Your future. Own them all on the new data intelligence platform",
    "sameAs": [
      "kg:/m/0120wgnc",
      "https://www.wikidata.org/wiki/Q18350420",
      "https://en.wikipedia.org/wiki/Databricks",
      "https://twitter.com/databricks",
      "https://www.databricks.com/feed",
      "https://www.youtube.com/c/Databricks",
      "https://www.facebook.com/pages/Databricks/560203607379694",
      "https://www.linkedin.com/company/databricks",
      "https://www.glassdoor.com/Overview/Working-at-Databricks-EI_IE954734.11,21.htm"
    ],
    "telephone": "+1-866-330-0121",
    "areaServed": "http://www.wikidata.org/entity/Q13780930",
    "legalName": "Databricks Inc.",
    "knowsLanguage": "en-US",
    "url": "https://www.databricks.com/",
    "additionalType": "https://www.wikidata.org/wiki/Q110029326",
    "logo": {
      "@type": "ImageObject",
      "width": "127",
      "height": "20",
      "url": "https://www.databricks.com/en-website-assets/static/8ed15a13c1511a75a4855999a2011c5c/f2f26/databricks-default.webp",
      "@id": "https://www.databricks.com/en-website-assets/static/8ed15a13c1511a75a4855999a2011c5c/f2f26/databricks-default.webp"
    },
    "contactPoint": {
      "@id": "https://www.databricks.com/#ContactPoint"
    },
    "address": {
      "@type": "PostalAddress",
      "streetAddress": "160 Spear Street",
      "postalCode": "94105",
      "addressRegion": [
        "https://www.wikidata.org/wiki/Q99",
        "California"
      ],
      "addressLocality": [
        "https://www.wikidata.org/wiki/Q62",
        "San Francisco"
      ],
      "addressCountry": "http://www.wikidata.org/entity/Q30",
      "name": "Databricks Address",
      "@id": "https://www.databricks.com/#PostalAddress"
    },
    "knowsAbout": [
      {
        "@type": "Thing",
        "sameAs": [
          "kg:/g/11khkg2rwf",
          "https://www.wikidata.org/wiki/Q117246174",
          "https://en.wikipedia.org/wiki/Generative_artificial_intelligence"
        ],
        "name": "Generative AI",
        "@id": "https://www.databricks.com/#Thing"
      },
      {
        "@type": "Thing",
        "sameAs": [
          "kg:/m/038_34",
          "https://en.wikipedia.org/wiki/Data_management",
          "https://www.wikidata.org/wiki/Q1149776"
        ],
        "name": "data management",
        "@id": "https://www.databricks.com/#Thing1"
      },
      {
        "@type": "Thing",
        "sameAs": [
          "kg:/m/0136zzks",
          "https://en.wikipedia.org/wiki/Data_lake",
          "https://www.wikidata.org/wiki/Q20707560"
        ],
        "name": "data lake",
        "@id": "https://www.databricks.com/#Thing2"
      },
      {
        "@type": "Thing",
        "sameAs": [
          "kg:/m/0h7m73m",
          "https://www.wikidata.org/wiki/Q2499178",
          "https://en.wikipedia.org/wiki/Cloud_database"
        ],
        "name": "cloud database",
        "@id": "https://www.databricks.com/#Thing3"
      },
      {
        "@type": "Thing",
        "sameAs": [
          "kg:/m/0mkz",
          "https://en.wikipedia.org/wiki/Artificial_intelligence",
          "https://www.wikidata.org/wiki/Q11660"
        ],
        "name": "artificial intelligence",
        "@id": "https://www.databricks.com/#Thing4"
      },
      {
        "@type": "Thing",
        "sameAs": [
          "kg:/m/01hyh",
          "https://www.wikidata.org/wiki/Q2539",
          "https://en.wikipedia.org/wiki/Machine_learning"
        ],
        "name": "machine learning",
        "@id": "https://www.databricks.com/#Thing5"
      }
    ],
    "image": {
      "@type": "ImageObject",
      "width": "1200",
      "height": "628",
      "url": "https://www.databricks.com/sites/default/files/2023-11/databricks-og-universal.png",
      "@id": "https://www.databricks.com/sites/default/files/2023-11/databricks-og-universal.png"
    },
    "@id": "https://www.databricks.com/#Organization"
  },
  {
    "@context": "http://schema.org",
    "@type": "SearchAction",
    "name": "Site Search: Databricks",
    "target": "https://www.databricks.com/search?type=pending&search={search_term_string}",
    "query-input": "required name=search_term_string",
    "@id": "https://www.databricks.com/#SearchAction"
  },
  {
    "@context": "http://schema.org",
    "@type": "WebSite",
    "potentialAction": {
      "@id": "https://www.databricks.com/#SearchAction"
    },
    "name": "Databricks",
    "url": "https://www.databricks.com/",
    "@id": "https://www.databricks.com/#WebSite"
  }
]
C
Brand Presence
Action
Site-name consistency, favicon, social image, meta tags, schema, and contact signals
REVIEW

Brand Presence

Your brand name differs across channels — visitors see inconsistent identity.

C

65/100

Site name appears as

Page titleDatabricks: Leading Data and AI Platform for Enterprises
og:site_nameDatabricks
twitter:site@databricks
Organization.name—

Inconsistent — names differ across channels

Brand assets

Favicon

15/15

covers multiple sizes + apple-touch-icon

Social share image

20/20

og:image + twitter:image set

Meta completeness

20/20

Organization schema

0/15

Contact info discoverable

5/10

contact page

Findings

  • Brand name differs across channels — users see inconsistent identity
  • No Organization schema — Google can't render your logo in the knowledge panel
  • Only partial contact info discoverable — consider adding a dedicated contact page or mailto/tel link

How consistently your brand appears across channels — shared link previews, structured data, favicon, contact info.

A+
Mixed Content
No mixed content detected — all resources use HTTPS.
PASS
No mixed content detected — all resources use HTTPS.
Info::
No mixed content detected — all resources use HTTPS
A
Open Graph
Open Graph tags are well configured for social sharing.
PASS
Open Graph tags are well configured for social sharing.
Info::
Missing og:type
The og:type tag helps social platforms categorize the content.

The og:type tag helps social platforms categorize the content.

Why this matters

Default og:type is 'website' but the right value (article, product, profile) unlocks richer metadata fields and higher engagement.

Learn more ▾

og:type controls which other og: fields a platform respects. og:type=article enables og:article:published_time, author, and section — surfaced in news cards. og:type=product enables price/availability fields surfaced by Pinterest and shopping integrations. Default 'website' silently disables those.

Source: Open Graph Protocol

Preview

www.databricks.com

Databricks: Leading Data and AI Solutions for Enterprises

Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

WWW.DATABRICKS.COM

Databricks: Leading Data and AI Solutions for Enterprises

Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

Databricks: Leading Data and AI Solutions for Enterprises

www.databricks.com

www.databricks.com

Databricks: Leading Data and AI Solutions for Enterprises

Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.

All checks on this page are automated. Results are estimates - run targeted manual reviews when the score affects a release decision.

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