Cloudera

AUGUST 26, 2021

Before we jump into the data ingestion step, here is a quick overview of how Ozone manages its metadata namespace through volumes, buckets and keys. . If created using the Filesystem interface, the intermediate prefixes ( application-1 & application-1/instance-1 ) are created as directories in the Ozone metadata store. s3 = boto3.resource('s3',

Data Science 107

Data Science Forecasting Metadata Machine Learning 107

Ontotext

SEPTEMBER 15, 2020

This means the creation of reusable data services, machine-readable semantic metadata and APIs that ensure the integration and orchestration of data across the organization and with third-party external data. This means having the ability to define and relate all types of metadata. Create a human AND machine-meaningful data model.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

AWS Big Data

JULY 20, 2023

The Hive metastore is a repository of metadata about the SQL tables, such as database names, table names, schema, serialization and deserialization information, data location, and partition details of each table. Apache Hive, Apache Spark, Presto, and Trino can all use a Hive Metastore to retrieve metadata to run queries.

Data Lake 77

Data Lake Metadata Data Processing Big Data 77

AWS Big Data

JANUARY 9, 2024

Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications.

Cost-Benefit 88

Cost-Benefit Visualization Modeling Machine Learning 88

O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. For machine learning systems used in consumer internet companies, models are often continuously retrained many times a day using billions of entirely new input-output pairs.

Management 332

Management Machine Learning Experimentation Metrics 332

Cloudera

SEPTEMBER 29, 2022

Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. The data product is not just the data itself, but a bunch of metadata that surrounds it — the simple stuff like schema is a given. It is also agnostic to where the different domains are hosted.

Data Architecture 73

Data Architecture Metadata Data Warehouse Sales 73

Cloudera

MARCH 9, 2021

In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. Atlas provides open metadata management and governance capabilities to build a catalog of all assets, and also classify and govern these assets.

Data Governance 93

Data Governance Metadata Enterprise Data Processing 93

Domino Data Lab

OCTOBER 1, 2020

Combining the power of Domino Data Labs with Okera, your data scientists only get access to the columns, rows, and cells allowed, easily removing or redacting sensitive data such as PII and PHI not relevant to training models. So what does this look like? client('s3') obj = s3.get_object(Bucket='clinical-trials',

Enterprise 105

Enterprise Metadata Cost-Benefit Data Processing 105

AWS Big Data

NOVEMBER 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault.

Enterprise 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

Ontotext

NOVEMBER 22, 2020

Semantic Objects and the Semantic Objects Modeling Language (SOML) is a simple way to describe business objects or domain objects. The Platform is able to generate the initial Semantic Objects model, which can be modified and extended by the business user without having to work directly with the underlying knowledge graphs.

Metadata 72

Metadata Cost-Benefit Unstructured Data Technology 72

CIO Business Intelligence

JUNE 6, 2023

Here are three examples of organizations that unlocked increased value from hybrid data models: A large African telecommunications company was able to build up its analytics once and then deploy them on whatever infrastructure was available in the specific country of the African continent. That means security, governance, and metadata.

Insurance 52

Insurance Metadata Data Processing Machine Learning 52

datapine

SEPTEMBER 29, 2022

These needs are then quantified into data models for acquisition and delivery. It involves: Reviewing data in detail Comparing and contrasting the data to its own metadata Running statistical models Data quality reports. The captured data points should be modeled and defined based on specific characteristics (e.g.,

Data Quality 241

Data Quality Metrics Data-driven Management 241

Smart Data Collective

APRIL 14, 2021

With this tool, analysts are able to visualize complex data models in Python, SQL, and R. it offers data connectors, visualization layers, and hosting all in one package, making it ideal for teams that are data-driven with limited resources. It also comes with data caching capabilities that enable fast querying.

Business Intelligence 133

Business Intelligence Dashboards Visualization Big Data 133

Rita Sallam

APRIL 2, 2023

Interpretation of our machine learning model suggests buying $50k in building coverage and $100k in warehouse content coverage, as the latter significantly boosts predicted flood claim payouts. Pattern-basis can also consist of gradual drift and shift of workload patterns and this can be built into a predictive efficiency model.

Optimization 52

Optimization Machine Learning Insurance Risk 52

Cloudera

MAY 12, 2021

2020 saw us hosting our first ever fully digital Data Impact Awards ceremony, and it certainly was one of the highlights of our year. Please note that use cases could include but are not limited to: risk modeling, sentiment analysis, next best action recommendation, anomaly detection, natural language generation, and more.

Digital Transformation 65

Digital Transformation Machine Learning Optimization Data Lake 65

AWS Big Data

MARCH 30, 2023

Amazon Elastic Kubernetes Service (Amazon EKS) is becoming a popular choice among AWS customers to host long-running analytics and AI or machine learning (ML) workloads. Solution overview ACK lets you define and use AWS service resources directly from Kubernetes, using the Kubernetes Resource Model (KRM). We use the s3.yaml

Data-driven 69

Data-driven Metadata Testing Management 69

AWS Big Data

MARCH 10, 2023

Iceberg employs internal metadata management that keeps track of data and empowers a set of rich features at scale. The transformed zone is an enterprise-wide zone to host cleaned and transformed data in order to serve multiple teams and use cases. Dimension-based models have been used extensively to build data warehouses.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

AWS Big Data

MARCH 13, 2024

In this model, the Lambda function is invoked for each incoming event. The Data Catalog provides metadata that allows analytics applications using Athena to find, read, and process the location data stored in Amazon S3. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

Analytics 91

Analytics IoT Metadata Internet of Things 91

Cloudera

JUNE 25, 2021

While using CDH on-premises cluster or CDP Private Cloud Base cluster, make sure that the following ports are open and accessible on the source hosts to allow communication between the source on-premise cluster and CDP Data Lake cluster. Hive database, table metadata along partitions, Hive UDFs and column statistics.

Data Lake 68

Data Lake Metadata Unstructured Data Management 68

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Instead, we must build robust ML models which take into account inherent limitations in our data and embrace the responsibility for the outcomes. There are models everywhere.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Octopai

NOVEMBER 24, 2021

If I’m a dinner host extraordinaire and actually use both sets of china, the extra resources spent moving the second one are a necessary investment. Amazon Redshift uses a pay-per-use model. Octopai makes migrating to Redshift much easier, faster, and less expensive. Here’s how: Simpler migration. than packing up and moving one set.

Data Warehouse 73

Data Warehouse Metadata Data Processing Reporting 73

AWS Big Data

APRIL 17, 2024

The following diagram illustrates an indexing flow involving a metadata update in OR1 During indexing operations, individual documents are indexed into Lucene and also appended to a write-ahead log also known as a translog. The replica copies subsequently download newer segments and make them searchable.

Optimization 110

Optimization Snapshot Metadata Cost-Benefit 110

AWS Big Data

MAY 2, 2023

The workflow steps are as follows: The producer DAG makes an API call to a publicly hosted API to retrieve data. This feature is particularly useful if you want to externally process various files, evaluate multiple machine learning models, or extraneously process a varied amount of data based on a SQL request. environment.

Testing 97

Testing Experimentation Management Metadata 97

Laminar Security

NOVEMBER 16, 2023

You can then use CSPM to check if your cloud resources that host or access this data are securely configured and comply with the relevant regulations or standards. While SIEM helps you collect and analyze security data from various sources, DSPM’s byproduct (metadata) helps you to further analyze security info from your cloud data.

Risk 59

Risk Cost-Benefit Dashboards Management 59

AWS Big Data

APRIL 25, 2023

AnyCompany’s marketing team hosted an event at the Anaheim Convention Center, CA. The AWS Glue crawler ( consumer-glue-crawler ) runs to update the metadata followed by the AWS Glue job ( consumer-glue-job ), which curates the data by applying the Do not call filter. Let’s take an example. Delete the CloudFormation stack.

Sales 69

Sales Visualization Software Marketing 69

Cloudera

NOVEMBER 12, 2020

Moving to a cloud-only based model allows for flexible provisioning, but the costs accrued for that strategy rapidly negate the advantage of flexibility. . This feature ensures workloads remain in context with all common data, including metadata management, data governance, and security policies. A solution. More than likely it is.

Data Warehouse 101

Data Warehouse Reporting Risk Cost-Benefit 101

AWS Big Data

FEBRUARY 1, 2024

Large language models (LLMs) are becoming increasing popular, with new use cases constantly being explored. This is where model fine-tuning can help. Before you can fine-tune a model, you need to find a task-specific dataset. Next, we use Amazon SageMaker JumpStart to fine-tune the Llama 2 model with the preprocessed dataset.

Modeling 92

Modeling Metadata Data Processing Unstructured Data 92

Cloudera

SEPTEMBER 1, 2020

With HDFS, Solr servers are essentially stateless, so host failures have minimal consequences. By encapsulating Kerberos, it eliminates the need for client software or client configuration, simplifying the access model. Coordinates distribution of data and metadata, also known as shards. Provides perimeter security.

Snapshot 66

Snapshot Unstructured Data Dashboards Interactive 66

AWS Big Data

OCTOBER 11, 2023

Also, a data model that allows table truncations at a regular frequency (for example, every 15 seconds) to store only relevant data in tables can cause locking and performance issues. The second streaming data source constitutes metadata information about the call center organization and agents that gets refreshed throughout the day.

Management 101

Management Metadata Analytics Dashboards 101

IBM Big Data Hub

APRIL 11, 2024

In the context of AI, it can refer to the safety and ethics guardrails of AI tools and systems, policies concerning data access and model usage or the government-mandated regulation itself. Bolster development teams by inviting diverse, multidisciplinary teams to join them in these workshops as they assess ethics and model risk.

Risk 77

Risk Consulting Modeling Data Processing 77

AWS Big Data

JANUARY 10, 2024

During the query phase of a search request, the coordinator determines the shards to be queried and sends a request to the data node hosting the shard copy. One notable drawback of this replication model is its susceptibility to slowdowns in the event of any impairment in the write path.

Metadata 92

Metadata Broadcasting Data Processing Modeling 92

AWS Big Data

MARCH 19, 2024

further simplifies integration with artificial intelligence (AI) and machine learning (ML) models, facilitating the implementation of semantic search. Combining lexical and vector search improves the quality of search results by using their best features in a hybrid model. OpenSearch Service 2.11 OpenSearch Service 2.11

Data Processing 68

Data Processing Modeling Machine Learning Metadata 68

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. High variance in a model may indicate the model works with training data but be inadequate for real-world industry use cases.

Enterprise 77

Enterprise Data Integration Data Quality Contextual Data 77

CIO Business Intelligence

MARCH 6, 2024

SAP announced today a host of new AI copilot and AI governance features for SAP Datasphere and SAP Analytics Cloud (SAC). We have cataloging inside Datasphere: It allows you to catalog, manage metadata, all the SAP data assets we’re seeing,” said JG Chirapurath, chief marketing and solutions officer for SAP. “We

Unstructured Data 118

Unstructured Data Dashboards Business Intelligence Data Governance 118

CIO Business Intelligence

APRIL 28, 2023

To better understand why a business may choose one cloud model over another, let’s look at the common types of cloud architectures: Public – on-demand computing services and infrastructure managed by a third-party provider and shared with multiple organisations using the public internet. Public clouds offer large scale at low cost.

Data Processing 54

Data Processing Metadata Cost-Benefit Risk Management 54

IBM Big Data Hub

MARCH 29, 2024

Instrumentation library: OTel provides an instrumentation model that runs on all platforms. Benefits of OpenTelemetry The OpenTelemetry protocol (OTLP) simplifies observability by collecting telemetry data, like metrics, logs and traces, without changing code or metadata. Prometheus uses PromQL to aggregate data and metrics.

Metrics 80

Metrics Visualization Measurement Optimization 80

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. Using ML models to search more effectively brought the search space down to 102—which can run on modest hardware. Model-Driven Data Queries.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105