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BI/Analytics

Looker

Keep the whole organization 
working from the same numbers.

Looker, from Google Cloud, is a BI platform built around a semantic model (LookML). By managing metric definitions centrally as code, it lets the whole organization always make decisions from “the same numbers.” It is strongest for organizations that value embedded analytics and governance.

What you can do with Looker

  • LookML (semantic modeling)

    Metric definitions are managed centrally as code. Definitions such as “sales” that tend to differ by department are unified, so the whole organization keeps using the same numbers.

  • BigQuery / Google Cloud integration

    Connects directly to Google Cloud data platforms such as BigQuery, running queries in the data warehouse itself to analyze large volumes quickly.

  • Embedded Analytics (embedded BI)

    Embed dashboards directly in your own services, including to offer analytics features in customer-facing products.

  • Looker Studio integration

    Combined with the free Looker Studio, you can scale from simple visualization to full semantic model operation as needed.

  • Governance and version control

    LookML is version-controlled in Git and updated safely through change history and review, preventing a sprawl of metric definitions and ensuring reliability.

  • Looker Blocks (industry templates)

    Modeling templates for each industry and use get your analytics foundation running faster than building from scratch.

Issues

Even with a BI tool in place, do these challenges remain?

Each department defines metrics differently, so the same name means different numbers

Even with the same KPI name, each department calculates it slightly differently, and reports go ahead without knowing which is right.

You want analytics in your own service, but lack embedded BI know-how

You want to offer dashboards to customers, but building them yourself takes too much effort and the approach is still undecided.

You have a data platform like BigQuery, but visualization and use haven’t followed

Data keeps building up in the warehouse, but dashboards and self-service analytics teams can actually use aren’t in place.

Looker solves all of these at once.

Benefits

Make “the same numbers” part of how your organization works, with ITSO.

01

Certified Google Cloud partner

As a certified Google Cloud partner, ITSO officially supports data platforms including Looker and BigQuery, from design to operation.

02

Expert LookML modeling

We unify metric definitions that differ by department into one semantic model, designing a foundation where the whole organization keeps using the same numbers.

03

Experience implementing Embedded Analytics

We design and implement dashboards embedded in your services, supporting you end to end in adding analytics to customer-facing products.

04

Building data foundations with BigQuery

We handle everything from adding Looker on top of your existing data warehouse to building the data foundation itself, including BigQuery.

05

Governance design and metric unification

We set up change reviews using LookML’s Git management, preventing a sprawl of definitions while widening use on the ground.

06

Ongoing maintenance and operation

Ongoing remote support for LookML changes, data connections and new models helps you keep expanding use.

Flow

Three steps to go-live, in as little as two months.

  1. 1

    Consultation and requirements

    2–4 weeks

    We organize the metrics to unify, data sources and whether embedded analytics is needed, and review your existing data platform, such as BigQuery.

  2. 2

    LookML modeling and dashboard development

    3–6 weeks

    We design and implement the semantic model in LookML and build dashboards from the requirements, with reviews under Git.

  3. 3

    Testing, rollout and adoption

    1–4 weeks

    After rollout to stakeholders and implementing embedded analytics, we go live, then follow usage and keep extending the model.

Scene

Looker is at work across a wide range of industries and tasks.

  • SaaS provider

    Customer analytics dashboards embedded in a product

    Looker dashboards were embedded in an existing service, giving customers a way to analyze their own data.

  • Corporate planning

    Company-wide metric definitions unified in LookML, cutting reporting work

    KPI definitions that varied by department were managed centrally in LookML, cutting the time spent reconciling numbers in meetings.

  • IT department

    A visualization layer on top of BigQuery

    Looker added an analysis layer on top of data that had been building up in BigQuery, encouraging self-service analytics on the ground.

Contact us

FAQ

  • Power BI is strongest in Microsoft environments and Tableau in Salesforce environments and advanced visuals, while Looker excels at central management of metric definitions with LookML and embedded analytics in your own services. It is especially suited to organizations using Google Cloud or BigQuery, or that value governance of metrics.

  • An implementation limited to one data source and set of metrics takes about 2–4 weeks. Plan on about 2–3 months for a standard implementation including broader LookML modeling and embedded analytics. We propose a separate roadmap depending on your data foundation.

  • Yes. Looker connects not only to BigQuery but to other cloud data warehouses and databases, so you can adopt it while making use of your existing data foundation.

  • With the Looker API, embedding is flexible, including design adjustments and access control. ITSO proposes the right approach for your requirements, such as iframe embedding or API integration.

  • LookML is a code-based modeling language, so some learning is needed. With ITSO’s managed support you can run it without dedicated engineers, and if you aim to bring it in-house, we also provide training and ongoing support.

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