Up to 20% of all employees in the United States are regularly late for work, costing organizations like yours billions of dollars a year. The solution? Timesheets, which monitor employee hours, tardiness, performance, and absenteeism. These documents also collect valuable data for payroll, accounting, billing, and project management. So they're critical for human resource teams everywhere. But there's a problem or two.

Today's apps provide users with convenience and flexibility. Even the way we handle finances and financial transactions is improved and expanded using top financial APIs.

2.5 quintillion bytes of data are produced every day, and those numbers are continually increasing. With such astronomical volumes of data, businesses have to understand and interpret data faster than ever before. However, data transfers must occur for businesses with millions of data entry points to properly store and interpret their data.

Consider for a moment, if you will, plastic patio furniture. Plastic Fantastic is a global manufacturer with several factories, warehouses, and plenty of stores. One can only imagine the sheer amount of data resulting from sales, production, suppliers, and finances. Everything that happens, from purchase and onward, to these chairs, tables, and cupboards in all corners of the world is measured.

Reverse ETL and customer data platforms (CDPs) are two big data trends that have been receiving a great deal of attention. While both CDPs and reverse ETL can help you make smarter data-driven decisions, there are also several crucial points of distinction. In this article, we’ll answer the question: what’s the difference between reverse ETL and a customer data platform?

Migrating analytics workloads to the public cloud has been one of the most significant big data trends in recent years—and it shows no sign of slowing down any time soon. According to a study by IT research company Forrester: Within three years, however, Forrester predicts that the fates will have reversed: Of course, before data can be processed in the public cloud, it has to get there in the first place via data migration.

On the surface, Talend seems like the ultimate data integration platform. It's open-source, maintains multi-cloud integration, supports data governance frameworks like GDPR and CCPA, and handles both ETL and ELT, providing you with more flexibility for data management. Dig a little deeper, though, and you'll notice this platform has an outdated user interface and limited capabilities, and you'll probably need to upgrade to its enterprise version to execute data integration.

Apache Hive and Apache HBase are incredible tools for Big Data. While there is some overlap in their functions, both Apache Hive and Apache HBase have unique qualities that make them better suited to specific tasks. Some key differences include: Ultimately, comparing Apache Hive to Apache HBase is like comparing apples to oranges or Google to Facebook. While the two entities are similar, they don't provide users with the same functionality.

APIs are powerful for ETL (extract, transform, load) and data integration workflows. API integrations make it possible for the seamless exchange of information between websites, databases, and applications. The Xplenty API allows you and your enterprise to monitor Xplenty clusters and jobs. Through the Xplenty data processing package and Xplenty web application, you can call the Xplenty API to.

Data warehouses fixed one aspect of the data silo problem but introduced another. They function as a large, single source of truth for your organization, but getting insights from this data in a typical Extract, Transform, Load (ETL) data pipeline requires the use of Business Intelligence (BI) and analytics platforms. By the time your data team creates these reports and sends them to other business units, it’s too late for daily decision-making.

“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” That’s according to the author and consultant Geoffrey Moore. It’s an unsettling thought given that data and analytics are shifting from a secondary activity to a core business function. So what can companies do to gather and harness all of this information? The below guide discusses data sources and their role in informing decision-making.

With over 100 out-of-the-box connectors, Fivetran is the no-code/low-code solution for many CTOs, software developers, and data analysts who want to extract, load, and transform data from disparate sources, load that data into a warehouse for analytics, and then convert it into a usable format.

While traditional ETL (Extract, Transform, Load) collects data within a centralized data warehouse, reverse ETL flips the target and destination of the standard ETL process. This allows information to be pushed out of data warehouses and into powerful third-party operational systems that can provide better analytics and reporting services. With the Xplenty platform and its ETL tools, all information is sent between warehouses and third-party operational systems in an efficient and secure manner.

If you're looking for a better way to organize your data and ensure it stays up-to-date, you need to start utilizing CDC processes today. Change data capture uses various techniques to detect changes made in source tables and databases in real-time. Read on to learn more about change data capture and how it can be implemented to better serve your business.

ETL Pipeline and Data Pipeline are two concepts growing increasingly important as businesses keep adding applications to their tech stacks. More and more data is moving between systems, and this is where Data and ETL Pipelines play a crucial role. Take a comment on social media, for example. It might be picked up by your tool for social listening and registered in a sentiment analysis app.

Data warehouses have made it easier for customers to store massive amounts of data. That information is useless, however, unless it is actionable. Making data actionable means employees can use the data for decision-making and improving the user experience. In this article, we’ll discuss reverse ETL, pushing data to Zendesk from your warehouse, and the value of this process.

Stitch is a popular cloud-based Extract, Load, Transform (ELT) tool. Stitch seamlessly moves data between databases, warehouses, data lakes, SaaS services, and other applications with no code required whatsoever, making it a valuable weapon for data integration. However, the platform has limited data transformation capabilities and, away from its free tier, charges users for the amount of data they use per month, which often works out to be more expensive than other pricing models in the ETL/ELT space.

Salesforce is a CRM, which stands for "customer relationship management," and it helps companies personalize their approach and services to better guide business decisions.

In today’s 24/7 digital world, real-time data is a necessity to stay relevant for today’s businesses. Companies who wish to remain competitive must be able to quickly respond to customer demand and adjust to market changes. Supplying business leaders with real-time information for informed decision-making can be a challenge with information spread among disparate systems.

The amount of big data that enterprises churn out is simply staggering. All this information is worthless unless organizations unlock its true value for analytics. This is where ETL proves useful. Traditional ETL (extract, transform, and load) remains the most popular method for moving data from point A to point Z. It takes disparate data sets from multiple sources, transforming that data to the correct format and loading it into a final destination like a data warehouse.

NetSuite is an enterprise resource planning (ERP) business management platform part of the Oracle enterprise software ecosystem. Although it's primarily intended for small and medium-sized businesses, organizations of all sizes and industries have successfully used NetSuite to balance their checkbooks, manage inventory, bill and invoice customers, and more.

Integration is a very important part of the business world, but integrating different functions can be difficult for those without a technical background. This article lists the top API integrations that can help you integrate your systems and make your experience as easy and hassle-free as possible.

Gartner predicts that by 2023, organizations that promote data sharing will outperform their peers on most business value metrics. According to Debra Logan, Gartner’s Research Vice President, “Data sharing is the way to optimize higher quality data and more robust data and analytics to solve business challenges and goals.” Given these numbers, it is clear that businesses will need to embrace application software integration as a core business strategy.

MongoDB vs DynamoDB: How do you choose between them? Whether you are a two-man team bootstrapping a proof of concept or an established one battling with high throughput and heavy load; this post can serve as a guidepost in your decision process. Before going into the details, a brief history lesson on how these technologies emerged is pertinent; you must understand the optimal conditions for running these systems and how they operate in the wild before making an informed choice.

According to Gartner, leading organizations in every industry are wielding data and analytics as competitive weapons. Companies that leverage data as a competitive differentiator will stand the best chance of acting faster on opportunities and responding to threats in a competitive marketplace. The problem is that most companies aren’t aware of the value of their data. As a result, they aren’t leveraging the full potential of their data to make informed decisions.

Sometime in 2019, Netflix cracked a conundrum that stumped them for years. The company had so much data about its content and subscribers, it had to sync multiple heterogeneous data stores like MySQL and Elasticsearch continuously, which brought seriously stressful challenges like dual writes and distributed transactions. So Netflix created its own CDC tool that processes captured log events in sequence and takes dumps for specific tables and primary keys of tables. Problem sorted. Case closed.

Imagine this: less than half an organization’s structured data is used in decision-making. Think of the missed opportunities for customer acquisition and revenue by not taking advantage of that information. According to an IBM study, 87 percent of CEOs regard data as a strategic asset. So why then are companies not harnessing the power of this information?

Reverse ETL is a data integration technology that offers a wonderful way to enable solutions for making various stored data more actionable and usable. This process is especially helpful for enterprise business operation tools that help teams execute processes and meet goals more effectively. The idea is to use clean and accurate data to enhance various SaaS platforms and business management tools to enhance processes.

REST API provides a solution for communicating easily with various apps, platforms, and web services. This tool allows the user to communicate and execute actions universally with various languages and more. Companies implementing REST API stand to gain a better experience and create more flexibility when using ERPs, CRMs, and more like Salesforce. When users connect to Salesforce with a REST API, they get more flexibility and options that make the process more actionable and streamlined.

Intercom bills itself as a “conversational relationship platform,” helping businesses connect with their audiences primarily through live chat, as well as email and chatbots. The Intercom platform offers functionality including engagement and onboarding for new customers, support for existing customers, and marketing for potential customers on the fence.

Change data capture is one of the fundamental underpinnings of modern data management. Without knowing when their enterprise data has changed or refreshed with new information, businesses wouldn’t be able to access up-to-the-minute insights that help them stay competitive in a constantly shifting landscape. In change data capture (CDC), users are promptly notified (either in real-time or near real-time) when changes have been made to a source table or source database.

In this guide, we'll discuss what a database schema is, six database schema designs, and how and why they are used. We know a lot of thought goes into database construction. Before creating any database, developers plan what it should include and how the different aspects work together. This planning ensures a database has the necessary design for its intended use. Coders then use the schema to implement the database’s design.

For organizations to succeed today, they have to make data-driven decisions and get the most value out of the information. “To monetize data, companies must first transform it so that it can be reused and recombined to enable new value creation.” Most organizations have a ton of information that is spread across multiple departments. Making sense of the information is no easy task. Inaccurate analytics or delayed insights can put the business in a vulnerable position.

Every computer application must have a method of storing, managing and using data. This requires an application and at least one database that can communicate with each other. Managing this connection can be difficult, especially with multiple databases. Fortunately, there are platforms that can manage databases and connections applications more efficiently. Heroku offers a Postgres management system for creating, managing, and using databases.

Organizations are losing out on data-driven decision-making opportunities when data stays in the data warehouse. While business intelligence solutions can surface insights from these data sets, it often reaches team members too late to be used for daily business operations. Reverse ETL empowers organizations to increase the value of their data warehouses through operationalization. Learn how this can transform the way companies use data and insights.