Tableau

MAY 11, 2022

Data fabrics do more than drive value with modern data management. In the past, data analysts and IT departments worked independently from one another, effectively decoupling the business’s data needs from IT’s governance and security rule-making.

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

Tableau

MAY 11, 2022

Data fabrics do more than drive value with modern data management. In the past, data analysts and IT departments worked independently from one another, effectively decoupling the business’s data needs from IT’s governance and security rule-making.

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

ODSC - Open Data Science

APRIL 3, 2023

As you’ll see below, however, a growing number of data analytics platforms, skills, and frameworks have altered the traditional view of what a data analyst is. Data Presentation: Communication Skills, Data Visualization Any good data analyst can go beyond just number crunching.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

ODSC - Open Data Science

MARCH 23, 2023

Open-source Data Lake Management, Curation, and Governance for New and Growing Companies Arjuna Chala, Associate Vice President at HPCC Systems and Special Projects, discusses the challenges associated with managing data lake technology for start-ups and rapidly-growing companies. Watch on-demand here.

Data Science 52

Data Science Data Lakes Machine Learning Machine Learning 52

Dataconomy

SEPTEMBER 4, 2023

Define data ownership, access controls, and data management processes to maintain the integrity and confidentiality of your data. Data integration: Integrate data from various sources into a centralized cloud data warehouse or data lake. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Flipboard

NOVEMBER 24, 2023

JuMa is a service of BMW Group’s AI platform for its data analysts, ML engineers, and data scientists that provides a user-friendly workspace with an integrated development environment (IDE). JuMa is now available to all data scientists, ML engineers, and data analysts at BMW Group.

ML 151

ML ML AWS AI 151

Alation

FEBRUARY 13, 2020

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

Data Lakes 64

Data Lakes Data Analysis Data Analysis Big Data 64

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Data Warehouse 52

Data Warehouse Data Lakes Data Governance Analytics 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

The “Number of Datapoints Processed” KPI shows the total number of data points the model has processed, and the “Anomaly Confidence Score” indicates the confidence level in predicting anomalies. The anomaly scores and decisions are visualized through a QuickSight dashboard connected to the Amazon S3 data using AWS Glue and Athena.

AWS 112

AWS ML ML Apache Kafka 112

Alation

JULY 19, 2022

Instead of spending most of their time leveraging their unique skillsets and algorithmic knowledge, data scientists are stuck sorting through data sets, trying to determine what’s trustworthy and how best to use that data for their own goals. The Data Science Workflow. Closing Thoughts.

Data Scientist 59

Data Scientist Data Quality Data Science Data Analyst 59

Alation

FEBRUARY 20, 2020

Data lakes, while useful in helping you to capture all of your data, are only the first step in extracting the value of that data. With Trifacta, a broad range of users can structure their own data for analysis.

Data Lakes 40

Data Lakes ETL Data Analyst Data Preparation 40

Pickl AI

FEBRUARY 21, 2023

The gathering of data requires assessment and research from various sources. The data locations may come from the data warehouse or data lake with structured and unstructured data. Data Preparation: the stage prepares the data collected and gathered for preparation for data mining.

Data Mining 52

Data Mining Data Mining Data Mining Data Scientist 52

Alation

FEBRUARY 13, 2020

Whether we’re speaking to data analysts or CDOs, data people almost instantly understand the value of the Alation Data Catalog. Faces light up when we describe how Alation helps enterprises find, understand, trust, use and reuse data.

Data Lakes 52

Data Lakes Data Analyst Analytics Analytics 52

ODSC - Open Data Science

DECEMBER 19, 2023

They use their knowledge of data warehousing, data lakes, and big data technologies to build and maintain data pipelines. Data pipelines are a series of steps that take raw data and transform it into a format that can be used by businesses for analysis and decision-making.

Data Scientist 96

Data Scientist Machine Learning Machine Learning AI 96

AWS Machine Learning Blog

JANUARY 4, 2024

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing with complex technical code, business users and data analysts can ask questions related to data and insights in plain language. Arghya Banerjee is a Sr.

SQL 139

SQL Database AI AI 139

Alation

FEBRUARY 20, 2020

The Sentient Enterprise requires everyone have access to real-time data and the information derived from it – from IT professionals and data analysts to the city employee, actuary, production line worker, salesperson and marketer. “The Journey to Sentience” Breakfast Panel and Book Signing.

Data Lakes 52

Data Lakes Data Analyst Analytics Analytics 52

Dataconomy

FEBRUARY 23, 2023

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

Big Data 91

Big Data Big Data Data Engineer Data Engineering 91

Alation

FEBRUARY 13, 2020

From modest beginnings as a means to manage data inventory and expose data sets to analysts, the data catalog has grown in functionality, popularity, and importance. Modern data catalogs—originated to help data analysts find and evaluate data—continue to meet the needs of analysts, but they have expanded their reach.

Data Lakes 52

Data Lakes Data Governance Data Science Data Analyst 52

Alation

JUNE 21, 2022

Over time, we called the “thing” a data catalog , blending the Google-style, AI/ML-based relevancy with more Yahoo-style manual curation and wikis. Thus was born the data catalog. In our early days, “people” largely meant data analysts and business analysts. Data engineers want to catalog data pipelines.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

Alation

MARCH 1, 2022

Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed). Time is money,” said Leonard Kwok, Senior Data Analyst, ARC. Alation has the broadest and deepest connectivity of any data catalog.

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

IBM Journey to AI blog

MARCH 14, 2024

With newfound support for open formats such as Parquet and Apache Iceberg, Netezza enables data engineers, data scientists and data analysts to share data and run complex workloads without duplicating or performing additional ETL.

AWS 93

AWS Database ETL AI 93

ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform.

AI 52

AI AI Data Science Machine Learning 52

Alation

APRIL 19, 2022

In that sense, data modernization is synonymous with cloud migration. Modern data architectures, like cloud data warehouses and cloud data lakes , empower more people to leverage analytics for insights more efficiently. Data modernization helps you manage this process intelligently.

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

Alation

JULY 7, 2022

To answer these questions we need to look at how data roles within the job market have evolved, and how academic programs have changed to meet new workforce demands. In the 2010s, the growing scope of the data landscape gave rise to a new profession: the data scientist. Supporting the data ecosystem.

Data Scientist 52

Data Scientist Data Analyst Analytics Analytics 52

Pickl AI

AUGUST 1, 2023

Key Components of Data Engineering Data Ingestion : Gathering data from various sources, such as databases, APIs, files, and streaming platforms, and bringing it into the data infrastructure. Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Alation

JANUARY 10, 2023

Regardless of which archetype a customer falls into, they each have the common goal of driving value through data. A data catalog provides them with the tools to achieve this goal. The value that can be derived is ultimately based on the customers’ ability to make use of their data and also the manner in which they choose to do so.

Data Lakes 52

Data Lakes Data Analyst Analytics Analytics 52

Alation

JUNE 9, 2021

We have an explosion, not only in the raw amount of data, but in the types of database systems for storing it ( db-engines.com ranks over 340) and architectures for managing it (from operational datastores to data lakes to cloud data warehouses). Today they have too much.

Data Governance 59

Data Governance Database Cloud Data Machine Learning 59

IBM Journey to AI blog

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization.

Data Quality 52

Data Quality Data Governance Data Scientist Data Wrangling 52

Alation

AUGUST 2, 2022

Customer centricity requires modernized data and IT infrastructures. Too often, companies manage data in spreadsheets or individual databases. This means that you’re likely missing valuable insights that could be gleaned from data lakes and data analytics.

Data Silos 52

Data Silos Data Lakes Data Analyst Data Scientist 52

Alation

SEPTEMBER 23, 2021

Data Catalogs for Data Science & Engineering – Data catalogs that are primarily used for data science and engineering are typically used by very experienced data practitioners. At minimal function, a data catalog should provide metrics that show who is querying a data set and how often.

Data Preparation 52

Data Preparation SQL Data Governance Data Analysis 52

Alation

MARCH 21, 2023

When it embarked on a digital transformation and modernization initiative in 2018, the company migrated all its data to AWS S3 Data Lake and Snowflake Data Cloud to provide accessibility to data to all users. Using Alation, ARC automated the data curation and cataloging process. “So

Analytics 52

Analytics Analytics Data Silos Big Data 52

Alation

NOVEMBER 28, 2022

But refreshing this analysis with the latest data was impossible… unless you were proficient in SQL or Python. We wanted to make it easy for anyone to pull data and self service without the technical know-how of the underlying database or data lake. Sathish and I met in 2004 when we were working for Oracle.

Data Governance 52

Data Governance Database Data Quality Data Lakes 52

Pickl AI

JUNE 28, 2023

Data cleaning, normalization, and reformatting to match the target schema is used. · Data Loading It is the final step where transformed data is loaded into a target system, such as a data warehouse or a data lake. It ensures that the integrated data is available for analysis and reporting.

Data Mining 52

Data Mining Data Mining Data Mining ETL 52

Alation

FEBRUARY 17, 2023

Can you differentiate between governance of raw data and enhanced data (information)? It is not uncommon, particularly with data lakes, to have different data stores and degrees of transformation. This is the idea of having data at a raw, semi-transformed, and consumption-ready level. Where do you govern?

Data Governance 52

Data Governance Data Quality Data Analyst Data Pipeline 52

The MLOps Blog

MARCH 21, 2023

Other users Some other users you may encounter include: Data engineers , if the data platform is not particularly separate from the ML platform. Analytics engineers and data analysts , if you need to integrate third-party business intelligence tools and the data platform, is not separate.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69

Flipboard

DECEMBER 4, 2024

The use of separate data warehouses and lakes has created data silos, leading to problems such as lack of interoperability, duplicate governance efforts, complex architectures, and slower time to value. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

Data Lakes 137

Data Lakes Data Warehouse AWS Database 137

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lakes 52

Data Lakes Data Governance Data Warehouse Business Intelligence 52