Knowledge Hut

JANUARY 19, 2024

Tools Used TIBCO PowerBI SAP Business Objects QlikSense Word processing MS Visio MS Office Tools Google docs Approach Business intelligence focuses on descriptive statistics. Business Intelligence v s Business Analytics: Definitions Business Intelligence refers to the process of gathering and analyzing data to make better business decisions.

Business Intelligence 52

Business Intelligence BI Business Analyst Aggregated Data 52

Rockset

JULY 21, 2022

All interactions are streamed in the form of semi-structured events into Firebase’s NoSQL cloud database, where the data, which includes a large number of nested objects and arrays, is ingested. Since we no longer have to set up schemas in advance, we can ingest real-time event streams without interruption into Rockset.

NoSQL 52

NoSQL IT MongoDB SQL 52

DoorDash Engineering

OCTOBER 17, 2023

SRM represents one of the most egregious data quality issues in A/B tests because it fundamentally compromises the basic assumption of random assignment. For example, if two reasonably sized groups are expected to be split 50/50, but instead show a 55/45 split, the assignment process likely is compromised.

Education 87

Education Kafka Algorithm Data Warehouse 87

Ascend.io

SEPTEMBER 14, 2023

The rise of data-intensive operations has positioned data engineering at the core of today’s organizations. As the demand to efficiently collect, process, and store data increases, data engineers have started to rely on Python to meet this escalating demand.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

DareData

JULY 5, 2023

In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently. To overcome this challenge, many companies are turning to Data Lake solutions, which provide a centralized and scalable platform for storing, processing, and analyzing data.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Rockset

AUGUST 30, 2021

However, for many use cases at huge volumes — such as a Kafka topic that streams tens of TBs of data every day — it becomes prohibitively expensive to index the raw data stream and then calculate the desired metrics downstream at query processing time. You can also optionally use WHERE clauses to filter out data.

SQL 52

SQL Kafka MongoDB MySQL 52

Confluent

FEBRUARY 6, 2019

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Rapid prototyping is typically used here.

Machine Learning 106

Machine Learning Python Kafka Java 106

Knowledge Hut

NOVEMBER 17, 2023

Building, installing, and managing data solutions on the Azure platform will be their responsibility. They will work with other data specialists to ensure that data solutions are successfully integrated into business processes. You ought to be able to create a data model that is performance- and scalability-optimized.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Rockset

DECEMBER 17, 2020

Overview of the Customer 360 App Our app will make use of real-time data on customer orders and events. We’ll use Rockset to get data from different sources and run analytical queries that power our app in Retool. From there, we’ll create a data API for the SQL query we write in Rockset.

Building 40

Building Aggregated Data SQL Data Ingestion 40

Knowledge Hut

SEPTEMBER 27, 2023

Speed QuickSight's in-memory processing, enhanced by SPICE, allows for quick data retrieval and analysis. This is particularly helpful for large datasets and real-time analytics Power BI optimizes data query performance, nonetheless, the complexity of calculations and data interactions may influence the speed.

BI 52

BI AWS Database-centric Data Lake 52

ProjectPro

DECEMBER 7, 2021

Data Pipeline Tools AWS Data Pipeline Azure Data Pipeline Airflow Data Pipeline Learn to Create a Data Pipeline FAQs on Data Pipeline What is a Data Pipeline? A pipeline may include filtering, normalizing, and data consolidation to provide desired data.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Netflix Tech

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

Process 84

Process Data Pipeline Datasets SQL 84

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. RDD uses a key to partition data into smaller chunks.

Big Data 52

Big Data Data Process Process Kafka 52

AltexSoft

DECEMBER 23, 2022

Integrating data from numerous, disjointed sources and processing it to provide context provides both opportunities and challenges. One of the ways to overcome challenges and gain more opportunities in terms of data integration is to build an ELT (Extract, Load, Transform) pipeline. Order of process phases. What is ELT?

Process 52

Process Building Raw Data Data Lake 52

Rockset

OCTOBER 4, 2022

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. ClickHouse has several storage engines that can pre-aggregate data.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

Rockset

AUGUST 12, 2019

As an example, let’s say we are organizing a charity fundraiser and want a live dashboard at the event to show the progress towards our fundraising goal. Your DynamoDB table for tracking donations might look like In this scenario, it would be reasonable to track the donations per platform and the total donated so far.

NoSQL 40

NoSQL AWS SQL Datasets 40

Snowflake

DECEMBER 6, 2023

This issue, and similar issues I’ve watched loved ones manage in the past, piqued my interest in healthcare data as a whole, particularly whole-person data. What’s the coolest thing you’re doing with data? We’re using healthcare event data to feed algorithms that act as a co-pilot for care managers.

Healthcare 90

Healthcare Aggregated Data Medical Data 90

Cloudera

JUNE 29, 2023

However, because most institutions lack a modern data architecture , they struggle to manage, integrate and analyze financial data at pace. Incorporate data from novel sources — social media feeds, alternative credit histories (utility and rental payments), geo-spatial systems, and IoT streams — into liquidity risk models.

Data Architecture 83

Data Architecture Architecture Management Banking 83

Picnic Engineering

OCTOBER 31, 2023

Installations and app instrumentation While installing the Datadog agent on a Kubernetes cluster using their official Helm chart is a straightforward process, configuring application pods can appear rather complex. The capability to aggregate data in one place, combined with a wide range of integrations, simplifies data collection and access.

Java 52

Java Aggregated Data Coding Python 52

Snowflake

JUNE 8, 2023

Similarly, we could create a product 360, pulling data from various production processes or software embedded in them, plus sales transactions, service records, and product usage. Those data products could be used by themselves or aggregated into an aggregate data product, like the customer 360 described above.

Aggregated Data 69

Aggregated Data Raw Data Telecommunication Data 69

LinkedIn Engineering

DECEMBER 20, 2023

Collecting signals is not just about quantity; it's about ensuring the diversity and quality of the data, and ensuring that the data is relevant, accurate, and reflective of the real-world activities of the member. We need systems to ingest, process, and analyze the data efficiently. Espresso , Venice , Rest.li

Building 91

Building Algorithm Kafka Machine Learning 91

Lyft Engineering

SEPTEMBER 27, 2022

The very first version (see Figure 1) was designed to consume events, convert data to ML features, orchestrate model executions, and sync decision variables to their respective services. This pipeline ingests tens of millions of events per second and processes them into machine learning features.

Kafka 52

Kafka Aggregated Data Machine Learning Architecture 52

ProjectPro

FEBRUARY 8, 2023

In 2023, more than 5140 businesses worldwide have started using AWS Glue as a big data tool. For e.g., Finaccel, a leading tech company in Indonesia, leverages AWS Glue to easily load, process, and transform their enterprise data for further processing. AWS Glue automates several processes as well.

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

OCTOBER 13, 2023

Regularly update them to ensure that your reports are always using the latest data. As you clean and transform your data, it's important to document the steps that you take. It is important to regularly check the quality of your data to ensure that it is free of errors and inconsistencies. Join the Power BI community.

BI 52

BI Business Analyst Datasets Raw Data 52

AltexSoft

OCTOBER 21, 2022

Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

Rockset

FEBRUARY 16, 2024

Furthermore, Rockset’s ability to pre-aggregate data at ingestion time reduced the cost of storage and sped up queries, making the solution cost-effective at scale. With Rockset’s flexible data model , the team could easily define new metrics, add new data and onboard customers without significant engineering resources.

Architecture 59

Architecture SQL Data Warehouse Database 59

Picnic Engineering

SEPTEMBER 8, 2022

Quick re-cap: the purpose of the internal pipeline is to deliver data from dozens of Picnic back-end services such as warehousing, machine learning models, customers and order status updates. The data is loaded into Snowflake, Picnic’s single source of truth Data Warehouse (DWH). Yet, some messages are destined for the DWH only.

Kafka 52

Kafka Metadata AWS Java 52

Rockset

MARCH 1, 2023

As a result, compute contention ensues, causing several problems for customers and prospects: User-facing analytics in my SaaS application can only update every 30 minutes since the underlying database becomes unstable whenever I try to process streaming data continuously.

Architecture 59

Architecture AWS SQL Cloud Storage 59

Netflix Tech

JULY 12, 2019

delivering a large amount of business value in the process. Gatekeeper accomplishes its prescribed task by aggregating data from multiple upstream systems, applying some business logic, then producing an output detailing the status of each video in each country. The team responsible for this curation is Title Operations.

Datasets 73

Datasets Kafka Architecture Aggregated Data 73

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. In the event that they are not the same, what are the difference s? To provide meaningful business insights, it collects and manages data from a variety of sources. Data Warehouse in DBMS: .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Rockset

NOVEMBER 1, 2022

Step 1: Data Acquisition Elasticsearch is rarely the system of record which means the data in it comes from somewhere else for real-time analytics. Rockset has built-in connectors to stream real-time data for testing and simulating production workloads including Apache Kafka , Kinesis and Event Hubs.

Database-centric 52

Database-centric Pipeline-centric SQL Aggregated Data 52

Scott Logic

JULY 26, 2023

Knowledge Graphs, to quote the Alan Turing Institute , “organise data from multiple sources, capture information about entities of interest in a given domain or task (like people, places or events), and forge connections between them.” It was hypothesised that in combination with the Knowledge Graph, the LLM (e.g.

Banking 52

Banking Aggregated Data Retail Architecture 52

Databand.ai

JULY 10, 2023

Data analysis: Processing and studying the collected data to recognize patterns, trends, and irregularities that can aid in diagnosing issues or boosting performance. Security: Observability platforms often include built-in security features to ensure the integrity and confidentiality of your data.

Data Pipeline 52

Data Pipeline Algorithm Raw Data Aggregated Data 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

SEPTEMBER 21, 2023

It interacts through comprehensive REST APIs , processing and returning results in JSON format. ESRE enables advanced relevance ranking, natural language processing (NLP), and the ability to work with large language models (LLMs) like OpenAI’s GPT-3 and GPT-4. Analysis of logs, metrics, and security events.

Engineering 52

Engineering NoSQL Programming Language Java 52

Confluent

MARCH 28, 2019

At Confluent, we want to help developers understand how to think about event streaming and the opportunities it can create. Educating people on what an event stream looks like is a daunting task. Traditionally, making sense of the data flowing in a distributed event streaming platform is done by charts and graphs of aggregated data.

Kafka 74

Kafka Aggregated Data Media Engineering 74

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52