Sprinkle Data

In this digital world, everyday great volumes of data are being generated from varied sources, and companies want to give this data a form and structure by assembling it in an organized way and at a unified place to use it to their advantage. They want to analyze their data further to get a good understanding and to make well-informed data-driven decisions. To bring meaning to this raw data, ETL tools play a significant role and help businesses to take data analytics to the next level. There are several ETL tools available in the market which automate this whole process of building data-pipeline, managing and monitoring them. In this article, we will understand the whole process of ETL in detail and ETL tools that are best suited to automate your data pipelines for accurate analysis. What is ETL?‍ ETL stands for “Extract, Transform and Load”. ETL is a process of extracting data from different data sources, cleansing and organizing it, and eventually, loading it to a target data w...

What is Snowflake? Snowflake is a cloud data platform that supports multiple features, including handling large workloads. It gives secured access to data, offering scalability and better performance, and its easy-to-use platform is delivered as a service (Saas). Snowflake provides software as a service model which requires little maintenance helping customers to only focus on accumulating value from data without focusing much on platform maintenance often these qualities are offered by the right data warehouse. Traditional data warehouses were inflexible, pricey, and difficult to use but modern data warehouses came to the rescue revolutionizing the cloud technologies offering pricing models according to requirements rather than a subscription model preventing customers from overpaying and a utilization model where one uses resources according to needs, providing great scalability. One such data warehouse is Snowflake which provides numerous features and functionalities hence helping...

Introduction Throughout the years, DevOps has proved to be a successful practice in optimizing the product delivery cycle. As years passed by and as enterprises throughout the world focused on building a data-driven culture, it was necessary to build it in a proper manner to reap the most benefits from one’s business data. Instead of optimizing with mere assumptions and predictions, these business data provided users with factual insights for best decision making.  Before we dive deep on how different DataOps is from DevOps, let me clue you in with a crisp explanation. DevOps is the transformation in the delivery capability of development and software teams whereas DataOps focuses much on the transforming intelligence systems and analytic models by data analysts and data engineers.  DevOps is a synergy of development, IT operations, and engineering teams with the main idea to reduce cost and time spent on the development and release cycle. However, DataOps works one le...

Introduction In today’s modern world where data is considered to be the most valuable company’s asset, there is a need to protect it from data breaches and damages. As we know with every problem comes a solution, so for this issue we have modern data warehouses with the best built-in functionalities to protect it from attacks and are used to manage the data effectively, one such warehouse is: Google BigQuery. Google BigQuery is a fully controlled enterprise data warehouse that aids in handling and examining data with built-in features like machine learning, data analysis, and business intelligence. Many firms use this data warehouse to implement data analytics use cases to help them make better informed decisions. It is a highly scalable and cost-effective data warehouse that supports many features directing businesses to progress in the right direction. Though BigQuery is fast and affordable, it can consume a lot of processing power if not used properly. To use GoogleBig query ...

  Introduction We can see a growing pattern of analysing one’s business data. This trend starts right from the biggest of enterprises to small startups. However, very big businesses could afford any analytic or reporting tools. Whereas SMEs and Startups find it hard to identify the best tool for their requirements which also fits into their budget.   We have analyzed the 5 best free or affordable SQL reporting tools and open source dashboard reporting tools for Startups and SMEs   l Sprinkle Data l Metabase l Chartio l Redash l Mode Analytics   Sprinkle Data Sprinkle is an all in one no-code data analytics tool. Provides ability to integrate, blend and model data without writing code. Pricing: Free plan, with paid plans starting from $200-$500   Pros: Does not require data to be loaded into a BI tool. Works directly on the data warehouse. Capable of connecting to a vast set of data sources like MySQL, Kafka, Kinesis, PostgreSQL, Hubspot, MongoDB, etc. See the co...