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9 AI Trends That Will Revolutionize Data Science

Data science is vital to business success. It’s our window into the likes and habits of our customers, creating opportunities to glean insights from the mountains of data we collect every day. Data has always helped businesses with decision-making, but AI is taking it a step further. So much so that today it can even be applied to the practice of creating impressive email subject lines. Machine learning for information management is now a key ally for every organization worldwide.

The Data Engineer's Crystal Ball: How Data Observability Helps You See What's Coming

Imagine you’re driving a car. You can see what’s happening on the road in front of you, but you have no idea what’s going on under the hood. It’s like driving blindly without any gauges or a dashboard to give you vital information. You don’t know how fast you’re going, how much fuel you have left, or if something is about to go wrong. In the same way, data engineers who lack data observability are like drivers with a limited view of the road.

Data 'Poka-Yoking' With Data Observability for the Modern Data Stack

While in the past, businesses used data to gain an edge over their rivals, in today’s competitive environment, data is imperative to stay in business. Modern businesses rely increasingly on data to manage all aspects of their operations, from everyday workflows to impacts on business strategy and customer interactions. As a result, data stacks have become extremely complex.

Offensive vs Defensive Data Strategy: Do You Really Need to Choose?

Deliberations about defining your data approach often revolve around an offensive vs defensive data strategy. Here, an offensive strategy is focused on driving positive outcomes through increased revenues and profitability or by providing an enhanced customer experience. The primary objectives of an offensive data strategy are typically tailored to the product or business side of the organization, prioritizing AI and analytics use cases to drive superior commercial or financial outcomes.

Are You Ready for the Data Quality Assessment?

The quality of your data determines how well it supports your business goals within a given context, be it in operations, planning, or decision-making. Low-quality data cannot effectively serve your purpose. Usually, decision-makers rely on data to support their decisions; however, much evidence suggests that poor or uncertain data quality can contribute to ineffective decision-making in practice.

Hevo

Automate and control end-to-end data pipelines - from combining raw data to driving last mile business actions - all within one intuitive, zero maintenance platform.

Streamlining eCommerce Data Analytics

eCommerce analytics involves tracking a wide range of metrics relating to the complete journey of the customer, right from discovery to acquisition, conversion, retention and advocacy. Analytics lays a foundation framework for any eCommerce business and it helps them understand which marketing and sales initiatives are working, those that aren't, and the areas that have a great potential for growth.

Automate your Reports on Google Sheets with Hevo Activate

Usually, your business users request you share the business reports in Spreadsheets. They are highly familiar with Sheets and prefer their reports on Sheets only. They assume delivering reports in XLS format is easy and quick. But, we understand the efforts and time required to export reports to Spreadsheets. Every time, you will have to run queries on your centralized data at the warehouse and then export results in XLS format. You may need to edit and update the Sheet regularly.

Building and Managing the Modern Datastore: The Data Lakehouse

The 'data lakehouse' is quickly becoming popular in the data analytics community. Data lakehouse architecture combines the benefits of a data warehouse and a data lake. It aims to merge the data warehouse’s data structure and management features along with the flexibility and relatively low cost of the data lake. Watch this panel discussion to learn how the data lakehouse can address the limitations of the data lake and data warehouse architecture to deliver significant value for organizations. Explore why the data lakehouse is an ideal option for enterprise data storage initiatives.