Lightcast Job Posting and Skills Data for Strategic Market Analysis Lightcast provides an invaluable resource for capital market analysts and investors by delivering detailed job posting and skills data. This data aids in assessing sector vitality and corporate health, allowing for strategic investment decisions. Some common uses cases include:

Sector Trends and Corporate Vitality Through Skills Analysis:

• Skills Demand Insight: Lightcast's job posting data includes a wide range of skills, from
  common competencies to specialized technical abilities. Analyzing the prevalence and
  variations of these skills across sectors can reveal significant insights into current and future
  market conditions. For instance, an increase in postings demanding cybersecurity skills may
  indicate heightened industry focus on data security.
• Technological Advancements: The demand for specific programming languages and software
  tools within job postings can provide a direct measure of technological adoption and
  innovation within sectors. This analysis helps predict sector growth and competitiveness.

Detailed Company Analysis with Integrated Identifiers:

• Linking Financial Data: Utilizing identifiers such as stock tickers, Figi IDs, and exchange data
  within Lightcast’s comprehensive database allows analysts to correlate job posting trends
  with financial performance metrics directly. This integration provides a unique perspective on
  company health and market potential.
• Robust Data Mapping: The inclusion of LinkedIn URLs and other digital footprints enables a
  thorough analysis of company strategies and workforce dynamics. This data helps in
  understanding how companies position themselves in the market, adapting to changing
  economic conditions.
• Strategic Data Application: By combining job and skills data with financial metrics, market
  participants can develop nuanced investment strategies, leveraging real-time data to
  capitalize on emerging opportunities and mitigate potential risks.

Optimal Data Delivery Mechanisms:

• Efficient Data Access via Snowflake: Lightcast’s use of Snowflake Direct Shares ensures that
  clients can access the latest job posting and skills data directly within their existing systems,
  facilitating immediate analysis and application.
• Flexible Integration with Bobsled: For clients requiring broader data accessibility, Lightcast
  employs Bobsled and other direct sharing mechanisms, which support seamless data
  integration across diverse cloud platforms. This flexibility is crucial for maintaining up-to-date
  market analyses and adapting investment strategies swiftly to reflect the latest labor market
  conditions.

Lightcast’s approach to job posting and skills data offers a foundational tool for financial
analysts and investors, providing a dynamic and detailed view of market trends and corporate
strategies through sophisticated data integration and delivery systems. This data is instrumental
in crafting informed, strategic decisions in the capital markets.

Caveats to Lightcast Big Data, and “point-in-time” clarity:

Lightcast maintains job posting data with certain fields that are considered "point-in-
time," meaning they remain unchanged with each update of the Job Posting Table. In the job
postings table, fields such as 'POSTED', 'EXPIRED', 'COMPANY_RAW', 'TITLE_RAW', and 'BODY'
are examples of this stability.

• The 'POSTED' field records the date a job was initially posted, and the 'EXPIRED' field notes
  the date the job posting was removed or expired, both of which do not change once set. This
  ensures these timestamps provide accurate historical snapshots of job availability and
  duration.
• The ‘COMPANY_RAW’ and ‘TITLE_RAW’ fields are un-enriched, original data fields that we
  offer to customers to maintain stability on the original hiring entity, and original title
  language offered to the public.
• Lastly, 'BODY' contains the full text of the posting from one of the sources, and this also
  remains unchanged. This field is important to many capital market customers who want to
  run their own analysis of the job posting information using home-grown keyword strings, or
  other techniques on the “raw” data.

It is important to note that the Lightcast data is not inherently point-in-time. The job
posting data is refreshed and enriched monthly, while the profile database is updated quarterly.

For clients who require a point-in-time dataset, it is recommended to unload the job
posting data monthly, and profile data quarterly. These data snapshots should be stored locally
to preserve historical context.

To aid clients in creating their own point-in-time datasets, Lightcast provides guidance on
utilizing the "pipeline runs" dates available in the "meta" tables. This enables clients to develop a
systematic approach to save data locally, ensuring a reliable point-in-time reference

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Posting Deduplication

https://kb.lightcast.io/en/articles/6957661-how-does-lightcast-handle-duplicate-postings

Lightcast Deduplication Process:

Lightcast’s database reflects a comprehensive collection of job listings posted across the
Internet. As such, robust processes are required to identify and remove duplicate listings.
Lightcast applies a unique two-step approach to deduplication, resulting in up to 80% of all
collected jobs being deduplicated. This ensures that our data is accurate and reliable for analysis.

1. Step One: On a source-level basis, we utilize intelligence within our scraping spiders to identify
   new advertisements specific to each source. The spiders are programmed to avoid collecting
   advertisements that have previously been aggregated, ensuring that only unique listings are
   collected initially.
2. Step Two: Given that the same advertisement can appear across multiple sources, we use
   normalized fields such as job title, company, and location to cross-check and identify duplicates.
   This process is conducted over a 60-day period to ensure comprehensive deduplication. For
   example, if a job for a Marketing Specialist at Google is first posted on March 1st, Lightcast
   considers this the ‘original posting’. Any identical advertisements found within the next 60 days
   are treated as duplicates. If Google posts the same ad every day for an entire year, Lightcast will
   count it six times, as a new cycle begins every 60 days.

Frequency and Updates: Our deduplication process is conducted daily and is regularly reviewed
and updated to maintain its accuracy and effectiveness.

Handling Complex Cases: For more complex cases, such as variations in job titles or minor
differences in postings, Lightcast employs advanced algorithms and manual review to ensure
accurate deduplication.

By implementing these stringent deduplication processes, Lightcast ensures that our job posting
data is as clean and accurate as possible, providing reliable insights for our users.

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All Active Job Postings

https://kb.lightcast.io/en/articles/6957675-job-posting-types-newly-posted-and-active

Job Posting Types: Newly Posted and Active

Within Lightcast job postings, we measure the number of job postings over a given timeframe in
two different ways.

• Newly Posted: This metric measures all postings that were posted within a specific month. It
  provides a clear view of the market's behavior during that particular month.
• Active: This metric measures how many postings were live during a specific month, even if they
  were originally posted in a previous month but left active by the employer. Active postings make
  use of our expiration methodology, which ensures that postings expire in a timely manner to
  prevent outdated listings from skewing data. In the United States, a date-based expiry is set at 61
  days. Our data collection process has been enhanced to more effectively validate if a posting
  remains active within this 61-day period. Lightcast continually works to improve our expiration
  methodology, and any improvements or market changes may cause variations in our active
  postings trend. While our tracking of expired postings is more accurate, trend lines may differ
  significantly as a result.
• Active Postings: These provide a comprehensive view of the total open demand present in a given
  month, offering valuable insights into ongoing job market trends.
• Newly Posted Postings: These offer a better understanding of the job market's behavior within a
  given month and over time, highlighting new opportunities as they arise.
  By using these two metrics, Lightcast offers a detailed and nuanced view of job market dynamics,
  helping users to understand both current demand and market behavior.

Company Based Monthly Job Postings Query

Description:

One popular use case is calling for the monthly job postings count from a specific company (Microsoft).

Data Shares Used:

• Job Postings
• Companies

SQL Example:

-- Set the ticker symbol
SET ticker = 'msft';

-- Query to get monthly posting counts by company / ticker
SELECT 
    DATE_TRUNC(MONTH, posted) AS pst_mth,
    COUNT(id) AS pst_cnt
FROM 
    lightcast.global.postings
WHERE 
    company IN (
        SELECT id 
        FROM lightcast.taxonomy.company
        WHERE 
            version IN (
                SELECT value 
                FROM lightcast.global.postings_meta 
                WHERE key = 'company_version'
            )
            AND tickersymbol IS NOT NULL
            AND tickersymbol = $ticker
    )
    AND posted >= '2024-03-01'
GROUP BY ALL 
ORDER BY 
    pst_mth ASC;