Lakebed is extremely flexible. The primary purpose of the app is easy data storage & access. It was built out of a recurring need to store data for building dashboards, reports, and data-driven apps.

Small & Medium Business

Goal: Spend less time finding business information, comparing various data points, and stressing about business.

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Context: Most small & medium business owners rely on accounting spreadsheets, bank statements, manager HR reports, and more to run their business. All this information spread across so many sources makes it time-consuming to review the health of the business and make data-driven decisions. Dashboards that bring all that information together in one place make it easy to keep up with business while enjoying a morning coffee. Reports can make data sharing with investors and partners quick and easy as well.

Federal Government Agency

Goal: Combine 6 files of 1.2 million rows of Government Open Data allowing communications and engagement staff to focus their efforts and tailor their message.

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Context: A federal agency has Open Data from various sources in six disparate text files. It took five minutes for an employee to add the files to a Lakebed installation. It then took 24 hours of automated processing for the server to load data into the data lake. The next day the data was available via an API, which an analyst used to build a search tool. Communications and engagement staff now consult this tool prior to visiting various cities and towns. This allows them to speak specifically about the government offices, number of government employees, the types of contracts being awarded, and the values of those contracts to local businesses.

Municipal Government Open Data

Goal: Reduce staff time spent cleaning, uploading, and hosting Open Data.

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Context: A municipal government made a commitment to provide Open Data to citizens. Data updates are infrequent because departments must send data to IT, which then removes various data, cleans it, and uploads large text files to the Open Data website server. Utilizing Lakebed, IT can set rules around data that is not to be included and columns to be renamed. Each department then adds their own data to the Lakebed data lake, which citizens can query via an API.

The added value of Lakebed is the ability to provide Open Data and completely separate internal data. Internal organization dashboards, data driven decisions, and business intelligence (BI) can easily leverage both the Open Data and the private, internal data.

Insurance Company Dashboards & Reports

Goal: Build near real-time management reports from multiple data sources.

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Context: An insurance company has separate systems for claims, accounting, policy issuance, and customer relationship management (CRM). These legacy systems have been built over time in-house and do not have APIs, but they can export data. Lakebed provides a single source of truth where the claims, underwriting, accounting, and other staff can drag & drop their own data files. Visual dashboards and reports query the Lakebed API to provide analysis almost immediately after data has been added to the data lake.

Using Lakebed the company could easily add Google Analytics data to draw correlations between website traffic, marketing and policies issued. Weather data could also be added to perform claims analysis of natural disasters like hurricanes and forest fires.

Marketing Analysis

Goal: Drop data from many different marketing channels into a data lake for easy, combined reports.

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Context: Organizations marketing across the many social media networks and other online channels end up with disparate data spread across all those channels. The only way to analyze effectiveness and make comparisons is to pull all that data into a single data lake. It is very quick and easy to add that data to Lakebed without writing a single line of code.

Medical Data Storage

Goal: A medical treatment provider hosts their own data lake, in-house, on a server in the corner of their office.

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Context: Patient data is extremely sensitive so cannot leave the protection of the providers own network. Cloud providers are not an option for this organization as they cannot guarantee the security of the cloud providers servers. Lakebed installations can run on any Linux or Windows server so this treatment provider can leverage the value of a data lake while significantly reducing the risk of a data breach and remain compliant with health data protection regulations.