BigQuery Studio lets analytics practitioners use SQL, Python, Spark or natural language directly within BigQuery, to streamline analytics workflows.

By integrating Vertex AI foundation models in BigQuery, you can analyze unstructured data from right inside BigQuery.

I’m calling it now. The next battleground for analytics adoption among business users will be the productivity suite. Let’s unpack that statement by considering these two examples: Traditional BI has always forced you down a one-way street for answers—drop what you are doing, login to the BI tool, and pray to the data deities that you can find the answer you’re looking for.

Kafka Connect is an open source data integration tool that simplifies the process of streaming data between Apache Kafka® and other systems. Kafka Connect has two types of connectors: source connectors and sink connectors. Source connectors allow you to read data from various sources and write it to Kafka topics. Sink connectors send data from the topics to another endpoint.

Introducing Confluent Platform version 7.5, which offers a range of new features to enhance security, improve developer efficacy, and strengthen disaster recovery capabilities. Building on the innovative feature set delivered in previous releases, Confluent Platform 7.5 makes enhancements to three categories of features: The following explores each of these enhancements and dives deep into the major feature updates and benefits.

In Part One of our “Inside Flink” blog series, we explored the critical role of stream processing and why developers are increasingly choosing Apache Flink® over other frameworks. In this second installment, we'll showcase how innovative teams across every industry and size are putting stream processing into practice – from streaming data pipelines to train ML models or more timely analytics to fraud detection in finance and real-time inventory management in retail.

In the digital age, data transfer is integral to operations for businesses of all sizes. While Extract, Transform, and Load (ETL) processes have become fundamental for moving raw data to destinations like data warehouses, the protocols you use to transfer these files can impact the efficiency and security of the entire operation. Dive into our comprehensive guide, as we shed light on the most popular file transfer protocols and their relevance in today's tech landscape.

In part one of this two part series, I reviewed the history of the chatbot, my 2003 patent, and the reasons why the conditions weren’t right for the type of chat experience we’re all now enjoying with ChatGPT. For part two, we get into what has changed and the different ways enterprises can drive modern chatbot experiences with ChatGPT.

The release of ChatGPT pushed the interest in and expectations of Large Language Model based use cases to record heights. Every company is looking to experiment, qualify and eventually release LLM based services to improve their internal operations and to level up their interactions with their users and customers. At Cloudera, we have been working with our customers to help them benefit from this new wave of innovation.

Hey there! Have you ever found yourself scratching your head over unpredictable cloud data costs? It’s no secret that accurately forecasting cloud data spend can be a real headache. Fluctuating costs make it challenging to plan and allocate resources effectively, leaving businesses vulnerable to budget overruns and financial challenges. But don’t worry, we’ve got you covered!

BigQuery ML inference engine lets you run inference over custom models, remote models, and pretrained models within your machine learning workflow.

You can now generate text embeddings in BigQuery and apply them to downstream application tasks using familiar SQL commands.

Use our latest dbt package to recreate your SAP extractor models and better understand your performance.

TraceMark’s sustainable sourcing monitoring platform provides transparency into global supply chains about the sourcing of raw materials.

Carto’s conversational GIS relies on BigQuery to provide information to generative AI, while BigQueryML connects to Vertex AI and PaLM2.

Learn the optimizations for a dbt deployment that are essential for a dependable data stack.

Since the introduction of stream processing, there have been three certainties in life: death, taxes, and out-of-order data. As a stream processing library built for Apache Kafka, Kafka Streams processes data in offset order. When out-of-order data is present, offset order differs from timestamp order and care must be taken to ensure that processing results respect timestamp order where appropriate.

Atlas AI‘s geospatial artificial intelligence platform that helps organizations anticipate changing societal conditions to help them make investment decisions.

The new BigQuery connector to Google Earth Engine improves ease-of-use and enables new analyses that combine raster and tabular data.

I recently watched the movie Air. I absolutely loved it. Note: if you don’t want spoilers, you may want to skip the next two paragraphs. Air is a story chronicling how Nike, the underdog in those days, steals Michael Jordan away from Adidas and Converse. With the cards stacked against Nike—they had a much smaller budget than their big-brand competitor, Adidas—it was conventionally assumed that Michael was better off signing with a more established brand.

Today we have exciting news to share with the debut of our new capacity model pricing for Qlik Analytics! This is an extension of our capacity model we introduced this spring for data integration. This is also the latest in a series of evolutions here at Qlik aimed at helping organizations more easily use data and analytics to better inform business decisions across any part of their organization.

In the past, it was commonly believed that only administrators or designated support contacts benefited from live product support. But that shortsighted view fails to acknowledge the reality that every user—be you an occasional business user, tenured analyst, or in-the-weeds IT administrator—can encounter roadblocks and require assistance. That's why our new In-App Support is available to all users worldwide, regardless of their role.

From MAR to syncs — learn all about Fivetran usage and pricing.

BigQuery, PubSub, Scheduler, Monitoring and more work together to make your DevOps processes easier with sampling data.

The new, automated open-source data migration tool moves Teradata, Hive, Redshift, and Oracle data warehouses from on-premises to BigQuery.

When it comes to geospatial data, BigQuery can help you store and analyze it, while Tableau can provide powerful visualization capabilities.

There's no denying that OpenAI's remarkable artificial intelligence applications (ChatGPT and DALL-E) have captured the zeitgeist and hurled the topic of Generative AI into every company boardroom. Conversations range from apocalyptic hand-wringing to blissful ignorance. I wonder if ChatGPT will single-handedly save the chatbot industry, or is this just another tech fad that will quickly wither and die?

Machine Learning (ML) is at the heart of the boom in AI Applications, revolutionizing various domains. From powering intelligent Large Language Model (LLM) based chatbots like ChatGPT and Bard, to enabling text-to-AI image generators like Stable Diffusion, ML continues to drive innovation. Its transformative impact advances multiple fields from genetics to medicine to finance. Without exaggeration, ML has the potential to profoundly change lives, if it hasn’t already.

It’s time to move your data transformations from stored procedures to a more modern approach with dbt™ and Fivetran.

From electronic medical records and monitoring devices, to personalized medicine and real-time decision-making, data is critical at every turn within modern healthcare. However, the sheer volume and complexity of healthcare data is posing increasing challenges on medical centers and professionals.

In today’s rapidly evolving digital landscape, businesses face numerous challenges when it comes to data management and protection. Defining effective backup, disaster recovery (DR), and business continuity objectives in particular, stand out as crucial. At Hitachi Vantara, we understand the importance of ensuring data resilience and uninterrupted operations for businesses that have embraced or are considering cloud or hybrid-cloud architectures.

Fivetran launches Terraform, Webhooks and Transformations APIs.

Here’s what customer loyalty looks like to us at Wellthy and the data-driven tactics we rely on to keep our customers coming back for more.

Generative AI (GenAI) has the potential to transform enterprise product operations, and as a Chief Product Officer (CPO), it’s essential to understand how to leverage generative AI to drive success within your product organization. This article serves as a comprehensive guide for how CPOs can use GenAI in product strategy, design, and innovation – generating new product ideas, creating unique designs, and exploring different variations and options.

Kensu is the first solution to bring advanced data observability capabilities to support Matillion, empowering organizations to gain richer insights into their data pipelines and ultimately strengthening trust and data productivity. Matillion ETL is a popular tool for building and orchestrating data integration workflows. It simplifies extracting data from various sources, transforming it according to business requirements, and loading it into a cloud data platform.

There was a huge amount of buzz about Apache Flink® at this year’s Kafka Summit London. From an action-packed keynote to standing-room only breakout sessions, it's clear that the Apache Kafka® community is hungry to learn more about Flink and how the stream processing framework fits into the modern data streaming stack.

At the beginning of my career as a data analyst, I had to rely on other team members when something went wrong in our data pipeline, often only finding out about it after the event. That experience was one of the driving factors for me to join Kensu. When I spoke with the team for the first time, I had that “lightbulb moment”: data observability is a way of providing help to various data team members, including data analysts, in making their lives more productive and less painful.

Read about how BigQuery now allows you to use manifest files for querying open table formats.

The data landscape is constantly evolving, and with it come new challenges and opportunities for data teams. While generative AI and large language models (LLMs) seem to be all everyone is talking about, they are just the latest manifestation of a trend that has been evolving over the past several years: organizations tapping into petabyte-scale data volumes and running increasingly massive data pipelines to deliver ever more data analytics projects and AI/ML models.

Google recently introduced significant changes to its existing BigQuery pricing models, affecting both compute and storage. They announced the end of sale for flat-rate and flex slots for all BigQuery customers not currently in a contract. Google announced an increase to the price of on-demand analysis by 25% across all regions, starting on July 5, 2023.

Data is a powerful force that can generate business value with immense potential for businesses and organizations across industries. Leveraging data and analytics has become a critical factor for successful digital transformation that can accelerate revenue growth and AI innovation.

What sets successful organizations apart from others today? They extract value from their data, turning it into an asset that helps drive the business forward. To get to that point, an organization — of any size — needs real-time, consistent, connected, and trusted data to support critical business operations and insights. However, many stumbling blocks can cause organizations to fail when executing their data strategy.

Artificial intelligence (AI) has become a driving force in the digital transformation of businesses across various industries. As Chief Information Officers (CIOs) strive to stay ahead of the AI hype cycle in today’s competitive landscape, harnessing generative AI in particular can help them achieve their enterprise AI goals – by transforming processes, boosting productivity, and enhancing decision-making.

‍ The mobile analytics stack isn't just about collecting data; it's about making sense of user behavior on your app. It's an amalgamation of various tools and techniques that allow businesses to gauge the effectiveness of their mobile applications, measure user engagement, and optimize for better performance.

Since the inception of our cloud journey, we have extensively utilized Let's Encrypt because it has been very reliable, fully automated, open, and free. Today, we’re proud to become an official sponsor of Let’s Encrypt. In this blog post, we’re celebrating this event by explaining our journey with Let’s Encrypt, how we integrate with their service, and why we chose them.

Learn how new SQL functions for BigQuery JSON give you more capabilities in dealing with JSON data.

Supply chain disruption continues to affect retailers, consumer packaged goods companies (CPGs), and customers. Constraints on the ability to produce goods have limited the availability of in-demand products, leading to inflation. Not only are manufacturers not making enough products in line with demand in industries such as automotive and electronics, at the same time, those products have become much more expensive.

The snapshots feature of the Apache Hadoop Distributed Filesystem (HDFS) enables you to capture point-in-time copies of the file system and protect your important data against corruption, user-, or application errors. This feature is available in all versions of Cloudera Data Platform (CDP), Cloudera Distribution for Hadoop (CDH) and Hortonworks Data Platform (HDP).

The conversation around generative AI naturally veers toward productivity, but people overlook this one, salient benefit: jumpstarting creativity. The best marketing combines data insights and creativity—and that’s where one of the many generative AI opportunities is for marketers.

Mapping out your SEO strategy? Here are the 42 most relevant SEO statistics you should know to ensure great rankings in 2023.

Picture it: You are the owner of a growing digital purveyor of premium baked goods. You see that your chocolate chip, macadamia nut cookies with a hint of coconut are going gangbusters whereas sales for peanut butter cookies are declining. This is bad for margins because the peanut butter cookies cost less to produce than the chocolate chip, macadamia nut, coconut cookies. You decide to offer a special coupon for your loyalty customers to grow the peanut butter cookie sales.

With the dramatic increase in the volume, velocity, and variety of data analytics projects, understanding costs and optimizing expenditure is crucial for success. Data teams often face challenges in effectively managing costs, accurately attributing them, and finding ways to enhance cost efficiency.

Fivetran’s Wizard for dbt Core™ VSCode extension enables data analysts to write more efficient models — all with a click of a button.

Marketing and sales is undergoing a profound transformation as generative AI (gen AI) paves the way for advancements and innovation. With gen AI, businesses are rethinking their approaches to customer experience, productivity, revenue, and growth in both the B2B and the B2C domains.

Do you aspire to create a product that's universally hated? Are you aiming to evoke feelings of exasperation, frustration, and downright dislike among your users? If you've been losing sleep, wondering how to really irk your user base, then this is the guide for you! In this rather unconventional manual, we’re going to flip the script and steer away from the age-old adage of 'the customer is always right'.

Built on BigQuery, Weather Source makes weather analytics simple and accessible so organizations can understand how weather impacts their business.

How our analytics engineering team uses ChatGPT to write the most efficient dbt packages for your most common analytics use cases.

Organizations across all industries are racing to understand large language models (LLMs) and how to incorporate the generative artificial intelligence (AI) capabilities provided by LLMs into their business activities. Thanks to LLMs’ broad utility in classifying, editing, summarizing, answering questions, and drafting new content, among other tasks they are being embedded into existing processes and used to create new applications and services.

Companies no longer question the importance of data analytics for their business success. With the help of data, brands can predict business outcomes, detect purchasing patterns, track customer behavior, and improve overall decision-making. However, many organizations still struggle with implementing the needed steps for robust data analysis. They often lack the time and expertise to use data to its fullest potential.