AWS Big Data

APRIL 29, 2024

The construction of big data applications based on open source software has become increasingly uncomplicated since the advent of projects like Data on EKS , an open source project from AWS to provide blueprints for building data and machine learning (ML) applications on Amazon Elastic Kubernetes Service (Amazon EKS).

Management 93

Management Big Data Metadata Data Warehouse 93

Cloudera

JUNE 3, 2022

Data scientists and machine learning engineers in enterprise organizations need to fully understand their data in order to properly analyze it, build models, and power machine learning use cases across their business. Once the session starts, CML shows the data connections from the project and offers snippets to create a connection.

Dashboards 92

Dashboards Visualization Machine Learning Data Science 92

datapine

MARCH 31, 2022

That’s where you come in. Let’s look at where a career in business intelligence currently sits in terms of salary and compensation. With an immense amount of job prospects, you can start as a junior employee and escalate to senior positions where you can manage your own teams and projects. First of all, SQL Programming.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Smart Data Collective

AUGUST 23, 2022

However, some companies have to learn the hard way that desiring to utilize big data is not enough. This entails using SQL servers appropriately. One of the things that you need to understand while running a data-driven company is how to use drop tables with SQL servers. Using Drop Tables for Your Data-Driven Business.

Big Data 89

Big Data Data Strategy Strategy Data-driven 89

AWS Big Data

AUGUST 7, 2023

Amazon Redshift ML makes it easy for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Amazon Redshift. With Redshift ML, you can take advantage of Amazon SageMaker , a fully managed ML service, without learning new tools or languages.

Forecasting 80

Forecasting Data Warehouse Machine Learning Modeling 80

Sisense

JANUARY 7, 2020

SQL is one of the analyst’s most powerful tools. In SQL Superstar , we give you actionable advice to help you get the most out of this versatile language and create beautiful, effective queries. The SQL order of execution defines the order in which the clauses of a query are evaluated. WHERE Clause. Creating order.

Optimization 104

Optimization IT 104

Cloudera

JUNE 7, 2021

At the end of March, we released the first version of Cloudera SQL StreamBuilder as part of CSA 1.3. It enabled users to easily write, run and manage real-time SQL queries on streams from Apache Kafka with an exceptionally smooth user experience. . Flink SQL DDL and Catalog support. Flink SQL DDL Support.

Analytics 106

Analytics Management IT 106

IBM Big Data Hub

APRIL 13, 2023

After developing a machine learning model, you need a place to run your model and serve predictions. Someone with the knowledge of SQL and access to a Db2 instance, where the in-database ML feature is enabled, can easily learn to build and use a machine learning model in the database.

Modeling 92

Modeling Statistics Machine Learning Testing 92

O'Reilly on Data

SEPTEMBER 15, 2021

The results gave us insight into what our subscribers are paid, where they’re located, what industries they work for, what their concerns are, and what sorts of career development opportunities they’re pursuing. The vast majority reported that they wanted to learn new skills (91%) or improve existing skills (84%).

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

AWS Big Data

DECEMBER 13, 2023

Data transform join – This is one of the submodules of the data transform module that can perform joins between the datasets using a custom SQL based on the metadata configuration. AWS Glue Studio provides the native SQL query visual transform, where a custom SQL query can be used to transform the source data.

Metadata 85

Metadata Data Lake Visualization Data Transformation 85

Cloudera

JULY 18, 2022

In this blog we will explore how we can use Apache Flink to get insights from data at a lightning-fast speed, and we will use Cloudera SQL Stream Builder GUI to easily create streaming jobs using only SQL language (no Java/Scala coding required). The streaming SQL job also saves the fraud detections to the Kudu database.

Analytics 91

Analytics Dashboards Statistics Visualization 91

Cloudera

MAY 1, 2023

release of Cloudera’s SQL Stream Builder (available on CDP Public Cloud 7.2.16 In this blog post, we will take a look at how these new concepts and features can help you develop complex Flink SQL projects, manage jobs’ lifecycles, and promote them between different environments in a more robust, traceable and automated manner.

Testing 79

Testing Management Data Processing IT 79

AWS Big Data

JANUARY 17, 2024

Create Hudi tables using the following Spark SQL. %%sql sql CREATE TABLE IF NOT EXISTS ${hudi_catalog}.${hudi_db}.${cow_table_name_sql}( sql INSERT OVERWRITE ${hudi_catalog}.${hudi_db}.${cow_table_name_sql} sql INSERT INTO ${hudi_catalog}.${hudi_db}.${cow_table_name_sql} HUDI_DATABASE}.{COW_TABLE_NAME_SQL}

Data Lake 90

Data Lake Snapshot Big Data Data-driven 90

AWS Big Data

OCTOBER 3, 2023

To learn more about the available optimize data executors and catalog properties, refer to the README file in the GitHub repo. SQL shell as shown in the following code. As of this writing, only the optimize-data optimization is supported. impl":"org.apache.iceberg.aws.s3.S3FileIO",

Optimization 107

Optimization Snapshot Data Lake Metadata 107

CIO Business Intelligence

JUNE 23, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. Warehouses are vertically integrated for SQL Analytics, whereas Lakes prioritize flexibility of analytic methods beyond SQL. Iterations of the lakehouse.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

CIO Business Intelligence

SEPTEMBER 14, 2023

This IT role requires a significant set of technical skills, including deep knowledge of SQL database design and multiple programming languages. Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. A bachelor’s degree in computer science is common.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. Warehouses are vertically integrated for SQL Analytics, whereas Lakes prioritize flexibility of analytic methods beyond SQL. Iterations of the lakehouse.

Data Lake 93

Data Lake Data Warehouse Machine Learning Cost-Benefit 93

AWS Big Data

MARCH 22, 2024

Trino is an open source distributed SQL query engine designed for interactive analytic workloads. On AWS, you can run Trino on Amazon EMR , where you have the flexibility to run your preferred version of open source Trino on Amazon Elastic Compute Cloud (Amazon EC2) instances that you manage, or on Amazon Athena for a serverless experience.

Metadata 87

Metadata Statistics Broadcasting Optimization 87

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. Source: RStudio.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

AWS Big Data

JULY 31, 2023

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. In this post, we show how you can migrate your existing SQL-based ETL workload to AWS Glue using Spark SQL , which minimizes the refactoring effort.

Sales 52

Sales Data Warehouse Visualization Testing 52

Cloudera

JUNE 28, 2022

In part two we will explore how we can run real-time streaming analytics using Apache Flink, and we will use Cloudera SQL Stream Builder GUI to easily create streaming jobs using only SQL language (no Java/Scala coding required). The streaming SQL job also saves the fraud detections to the Kudu database. The use case.

Dashboards 85

Dashboards Machine Learning Statistics KPI 85

AWS Big Data

OCTOBER 26, 2023

Data analysts and database developers want to use this data to train machine learning (ML) models, which can then be used to generate insights on new data for use cases such as forecasting revenue, predicting customer churn, and detecting anomalies. We also need an offline feature store to store features in feature groups.

Modeling 63

Modeling Data Warehouse Machine Learning Testing 63

Smart Data Collective

MAY 29, 2023

With the introduction and use of machine learning, AI tech is enabling greater efficiencies with respect to data and the insights embedded in the information. Further research will help to formulate a deeper clarification of what and where to find the right person for the job.

Data Collection 78

Data Collection Big Data Statistics Software 78

IBM Big Data Hub

OCTOBER 18, 2023

On December 5–6, 2023 at the Computer History Museum in Mountain View, CA, hundreds of developers and software engineers will come together at PrestoCon 2023 to support and learn more about Presto, the open-source SQL query engine for data analytics and the Open Data Lakehouse.

Statistics 94

Statistics Software Data Analytics Analytics 94

Jet Global

AUGUST 4, 2023

Various Paths to Work with Data Many different paths exist for learning to work with data. Learning to work with data involves developing the technical skills to manage large data sets and the soft skills to use storytelling and influencing to help audiences make data-informed decisions. The beauty of Modern Excel is two-fold.

Data Analytics 52

Data Analytics Analytics Finance Visualization 52

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. Another example is an AI-driven observability and monitoring solution where FMs monitor real-time internal metrics of a system and produces alerts.

Data Lake 87

Data Lake Unstructured Data Management Modeling 87

AWS Big Data

NOVEMBER 9, 2023

dbt enables you to write SQL select statements, and then it manages turning these select statements into tables or views in Amazon Redshift. dbt’s SQL-based framework made it straightforward to learn and allowed the existing development team to scale up quickly. It’s raw, unprocessed data straight from the source.

Data Warehouse 102

Data Warehouse Testing Data Quality Reporting 102

AWS Big Data

APRIL 25, 2024

Solution overview For this post, we consider a use case where a data engineering team wants to build an ETL process and give the best experience to their end-users when they want to query the latest data after new raw files are added to Amazon S3 in the central account (Account A in the following architecture diagram).

Metadata 101

Metadata Data Processing Management Testing 101

AWS Big Data

OCTOBER 17, 2023

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. AWS Schema Conversion Tool (AWS SCT) could help you with initial bulk load from Azure Synapse Analytics, BigQuery, Greenplum Database, IBM Netezza, Microsoft SQL Server, Oracle, Snowflake, Teradata and Vertica.

Data Warehouse 82

Data Warehouse Data Processing Data Lake Management 82

Business Over Broadway

JANUARY 11, 2021

Data professionals of all stripes, including data scientists, machine learning engineers and others, use different types of tools in their jobs. A recent survey of over 20,000 data professionals by Kaggle revealed that Python, SQL and R continue to be the most popular programming languages. Programming languages used in 2020.

Machine Learning 56

Machine Learning Data Science Software IT 56

Data Science 101

MAY 6, 2019

The big problem that we were solving at Mercedes is basically: how do you build machine learning into an environment where there’s limited-to-no data connectivity? That’s a great question and I think I would add another piece to that, which is that it kind of depends on where you’re at. Before Google, you worked at Mercedes.

Data Science 98

Data Science Modeling Machine Learning Testing 98

Jen Stirrup

SEPTEMBER 25, 2020

Certainly, if you take a look at some of the discussion on social media, it doesn’t take long to see that the SQL Family / Data Platform discussions online have become very heated. The SQL Community was a good place to start at the time, and I met a lot of people and made a ton of friends. I have had enough.

Data Science 92

Data Science IT 92

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Apache Iceberg overview Iceberg is an open-source table format that brings the power of SQL tables to big data files.

Data Lake 99

Data Lake Sales Data Warehouse Snapshot 99

Smart Data Collective

APRIL 14, 2021

This data can also make it easy for you to know where and why you might be losing clients. It comes coded in LookML, an SQ-like language that requires learning to set up. With this tool, analysts are able to visualize complex data models in Python, SQL, and R. Boost revenue.

Business Intelligence 134

Business Intelligence Dashboards Visualization Big Data 134

Cloudera

JANUARY 6, 2021

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Configuration: F irst, HBase and Spark need to be configured together for Spark SQL queries to work properly. Introduction. Python 3 is installed on each node at the same path.

Machine Learning 133

Machine Learning Data Science Management Enterprise 133

Jen Stirrup

MAY 5, 2020

For example, we can use HBase, which is a no SQL distributed database which offers random access to large amounts of data. It has native integration with other data sources, such as SQL Data Warehouse, Azure Cosmos, database storage, and even Azure Blob Storage as well. That includes very hot data sources such a real-time processing.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

Smart Data Collective

DECEMBER 21, 2021

Collecting and parsing this information can make it useful and AI offers learning capabilities to recognize trends and adapt customer interactions accordingly. But you also need a good database foundation to ensure that the data the AI is reading and learning from is good, accurate data. Databases in the Big Data Era.

Big Data 129

Big Data IoT Cost-Benefit Interactive 129