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Our latest Blogs & News
SAP Ariba Total Spend Analysis with Precog
Precog is excited to announce support for SAP Ariba! Using Precog, you can now access your SAP Ariba data in SAP Data Warehouse Cloud, SAP Analytics Cloud, Snowflake, Redshift, Power BI, Tableau, and more!
New Rules for Modern Data
The new world of data has new rules that might seem scary at first, but it doesn’t have to be that way. The trick is to use a tool — like Precog — explicitly designed for the world where data is messy, experts are expensive, and agility is vital.
Precog Enables Tableau Customers to Access 1000s More Data Sources
The latest release of Precog AI-powered Data Loader has enhanced support for Tableau and Tableau Data Prep, allowing end users unprecedented access to 1000s more data sources.
Introduction to JSON and NoSQL data
JSON and NoSQL datasets come in many forms. Some datasets are essentially tabular. Others are complex multidimensional structures.
Precog Partners with SME
Precog, the company behind the popular Precog solution for transforming and loading complex data for analytics and data science, has partnered with SME Solutions Group, Inc. based in Tampa, Florida.
Accessing the C3.ai Covid Data Lake
Precog opens up the C3.ai Covid Data Lake to millions or new users that don’t have the technical expertise to work directly with the API documentation and Python tools provided by C3.
Talend vs. Precog – ETL for JSON Comparison
Talend’s lengthy solution requires us to write Java and build a complex workflow in order to get results. The entire process… took 8 days. Precog enables us to complete the same task in 5 minutes…
AI for Data Integration
What is AI for Data Integration? It’s really about understanding the relationships between the data regardless of structure, and above…
Precog: Uniform Access to Any API
Precog provides a single solution for streaming API data from the source, transforming it into analytics-ready tables, and loading it into your target destination.
JSON to Insights: Analysing the Tabulated Data with Power BI
Now that the data has been tabulated, we can analyse it using software such as Microsoft Power BI.
JSON to Insights: More Details About Precog
Tables in Precog are streaming and virtualised. We can think of this as though the Precog table were a grocery list rather than the groceries themselves. We can use the same list in different stores the same way we can use the same Precog table with different datasets. We can also export tables and import them into different copies of Precog.
JSON to Insights: Analysing the Tabulated Data with SQL
Using Precog we can push the tabulated data into SQL databases and warehouses such as Snowflake and Postgres.
JSON to Insights: Joining Datasets with Precog
Precog shows us that in the adverse events dataset, drug characterizations are denoted as numbers. These numbers represent whether or not the drug was suspected as causing the adverse reaction or interacting with a suspected drug.
JSON to Insights: Tabulating Non-tabular Data Without Precog
Precog empowers even non-technical users to easily browse and curate tables from non-tabular data and load these tables directly into software such as Power BI and Tableau, databases such as Postgres and warehouses such as Snowflake.
JSON to Insights: Analysing Non-tabular Healthcare Data
This article follows in Keshav’s footsteps, showing how to derive insights from JSON healthcare data using Snowflake and Precog.
JSON to Insights: Tabulating Non-tabular Data with Precog
With Precog, we connect directly to the source of the data. In this case the source is the FDA.gov Web API. This ensures that we are always working with the latest data including new records and corrections.
Turbocharge Your ThoughtSpot!
Using Precog is as easy as “connect – pick – load – analyze” your data as shown below. No coding, complicated scripts, clunky SSH clients or anything else technical to learn or use.
AWS GuardDuty Security Dashboard
Engineered to transform variable, complex JSON data, Precog draws source data from file output, API URLs, and data repositories such as AWS S3 and Azure Blob Storage.
Ingesting JSON as Analytic Ready Tables into SQL Server Using Precog and Azure Data Factory
The Precog solution enables data analysts and engineers to access complex JSON data as tables. In many cases we want those tables to be stored in Microsoft SQL Server or some other SQL database engine. Such requirement can be implemented easily using Precog and Azure Data Factory.
Data Science On JSON Using Precog Precog and RStudio or Jupyter Notebooks
Whether you’re a professional data scientist or studying to become a data scientist, you’ll likely need to work with a JSON dataset. JSON isn’t easy to work with. It’s not tabular, and you can’t just push it to a SQL database — at least not without a “bit” of work.
Turn any API Into An Analytic Ready Data Source
There are over 200,000 API?s on the web today, and more being added all the time. And the vast majority of these API?s provide JSON data via a REST interface. Unless you are a developer you generally can?t do much with this data or get any value from it. API?s are by design built for developers.
Reinventing ETL On A New Mathematical Foundation
The Multidimensional Relational Algebra, or MRA, is at the core of everything we do at Precog. It’s what enables our product to provide such a smooth and intuitive user experience.
Why Organizations Want To Solve The JSON Problem
JSON stands for JavaScript Object Notation, and it?s a way to format data. It was developed in the early 2000s, but it?s only in the last few years that it?s really caught on. JavaScript spec now includes a JSON object, and many developers are incorporating JSON as a sort of subset of the language itself.
What To Do When You Don’t Have A Data Integration Engineer
You’ve probably been hearing about “big data” for a while now ? the term has been around for years, and in the meantime, data has only gotten bigger. A whole industry has sprung up around it, from collection to storage to analytics, and data integration engineers are part of that puzzle. But what if your company doesn’t have one?
The Final Frontier ? The Missing Link In ETL/ELT
The ETL (extract, transform, load) industry has been around for decades. Its primary purpose is to move data from source locations to data warehouses so analytics and data science teams can access the data in one place and perform analysis across a range of critical data sources.
Alteryx Macro for Massive Complex Data Sets
Are you trying to work with huge complex data sets in Alteryx Designer? Would you like to? Would you like to increase processing performance of Designer by 100x for many data sets? Would you like to be able to connect to live data sources like API’s or MongoDB?? Then the Precog Macro for Alteryx Designer can help.