Sisense

MARCH 30, 2021

In Gartner’s Top 10 Data and Analytics Trends for 2021, trend No. 9 is “dashboards will be replaced with automated, conversational, mobile, and dynamically generated insights customized to a user’s needs and delivered to their point of consumption.” Advanced data transformation with Custom Code.

Dashboards 52

Dashboards Machine Learning Data Warehouse Marketing 52

Sisense

OCTOBER 15, 2020

Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. Streaming data analytics is expected to grow into a $38.6 billion market by 2025. Let’s look at a few ways that different industries take advantage of streaming data.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 100

Data Warehouse Testing Data Quality Reporting 100

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics?

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Cloudera

FEBRUARY 8, 2021

RNN in general (recurrent neural networks) and LSTM specifically works very well with time-series data. For the avoidance of doubt, we are not purporting to be stock market experts, and nothing in this blog post should be taken as financial advice in any way. b) Basic data transformation. Go to runner.py and run it.

Machine Learning 72

Machine Learning Statistics Modeling Dashboards 72

Sisense

APRIL 10, 2020

In this article, we discuss how this data is accessed, an example environment and set-up to be used for data processing, sample lines of Python code to show the simplicity of data transformations using Pandas and how this simple architecture can enable you to unlock new insights from this data yourself.

Visualization 105

Visualization Reporting Data Processing Dashboards 105

Alation

JANUARY 17, 2023

These help data analysts visualize key insights that can help you make better data-backed decisions. ELT Data Transformation Tools: ELT data transformation tools are used to extract, load, and transform your data. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Bindu Chandramohan, Lead, Data Analytics, Alation : Thanks, Jason!

Metrics 52

Metrics Dashboards Sales Reporting 52

AWS Big Data

NOVEMBER 13, 2023

The upstream data pipeline is a robust system that integrates various data sources, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK) for handling clickstream events, Amazon Relational Database Service (Amazon RDS) for delta transactions, and Amazon DynamoDB for delta game-related information.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88

DataKitchen

OCTOBER 25, 2022

He thinks he can sell his boss and the CEO on this idea, but his pitch won’t go over well when they still have more than six major data errors every month. DataOps Observability Starts with Data Journeys. Jason considers his dashboard idea but quickly realizes the complexity of building such a system.

Testing 130

Testing Data-driven Visualization Dashboards 130

Anmut

APRIL 6, 2022

Here’s an example: Your customer data set , sales history data set , and service records are all collections of useful data elements. If you replace ‘asset’ with ‘data asset’ in the previous sentence, the notion of treating data as an asset makes perfect sense. Data transformation is a marathon, not a sprint.

Cost-Benefit 52

Cost-Benefit ROI Sales Data-driven 52

O'Reilly on Data

JANUARY 17, 2023

At best, you’ll get a model you can put in production right now (short time-to-market), buying your team the time to custom-tune something else (to get better performance). That takes us to a conspicuous omission from that list of roles: the data scientists who focused on building basic models. It does not exist in the code.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

AWS Big Data

MARCH 3, 2023

Initially, Tricentis defines these dashboards and charts to enable insight on test runs, test traceability with requirements, and many other pre-defined use cases that can be valuable to customers. As the files are created, another process is triggered to load the data from each customer on their schema or table on Amazon Redshift.

Software 52

Software Data Lake Testing Cost-Benefit 52

Sisense

DECEMBER 12, 2019

Will every department need access to BI and dashboards? Executive dashboards : BI access is limited to the C-level, providing execs with a real-time, big-picture look at company performance. A bright, shiny BI tool that’s perfect for creating beautiful visual reports might be a dud when it comes to tackling complex data.

Business Intelligence 88

Business Intelligence Software Data-driven Visualization 88

bridgei2i

SEPTEMBER 3, 2020

Now, the ability to respond very quickly, changing customer preferences, disruptions in the market, supply chain challenges means that you have to really think to what value you’re able to get to each of these singularly and together as an ecosystem. So the best way to do that is if you have the right digital building blocks.

Enterprise 94

Enterprise Insurance Digital Transformation Interactive 94

FineReport

MARCH 31, 2024

In today’s dynamic business landscape, Business Intelligence (BI) tools are indispensable software applications crafted to extract, transform, and present data, facilitating strategic decision-making. Best BI Tools for Data Analysts 3.1 Why is Choosing the Best BI Tools Important?

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

CIO Business Intelligence

APRIL 30, 2024

For example, a marketing executive could use the feature to ask, “Which market is contributing the most to lead gen in my campaign?” This feature enables users to save calculations from a Tableau dashboard directly to Tableau’s metrics layer so they can monitor and track the information over time. Metrics Bootstrapping.

Analytics 96

Analytics Metrics Visualization Dashboards 96

CIO Business Intelligence

JANUARY 24, 2024

Gather/Insert data on market trends, customer behavior, inventory levels, or operational efficiency. IoT, Web Scraping, API, IDP, RPA Data Processing Data Pipelines and Analysis Layer Employ data pipelines with algorithms to filter, sort, and interpret data, transforming raw information into actionable insights.

IoT 119

IoT Machine Learning Optimization Internet of Things 119

AWS Big Data

APRIL 5, 2023

Showpad aligns sales and marketing teams around impactful content and powerful training, helping sellers engage with buyers and generate the insights needed to continuously improve conversion rates. In 2021, Showpad set forth the vision to use the power of data to unlock innovations and drive business decisions across its organization.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

IBM Big Data Hub

JUNE 15, 2023

To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform. New insights are found in the combination of new data with existing data, and the identification of new relationships.

Data Warehouse 99

Data Warehouse Data Lake Optimization Data-driven 99

AWS Big Data

SEPTEMBER 19, 2023

This creates a more competitive market with better, lower-cost options for everyday Americans who aren’t being served well by traditional banks. As a result, end users were able to define jobs with declarative YAML configurations and define transformation logic with SQL.

Analytics 75

Analytics Risk Big Data Machine Learning 75

Jet Global

MAY 28, 2019

A data warehouse is typically used by companies with a high level of data diversity or analytical requirements. Organizational alignment will be at an all-time high as siloed departments are finally able to use the same data to reach the same conclusions.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

Birst BI

FEBRUARY 25, 2020

What gaps does the joint solution address in the market? The benefits of Birst’s cloud-native analytics platform powered by Snowflake’s world-class cloud data warehouse are numerous, especially as cloud becomes the first choice for enterprise data transformation initiatives.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

Jet Global

OCTOBER 30, 2023

This shift toward these stand-alone business intelligence tools is motivated by a need for rapid, informed decision-making in the competitive business landscape, allowing organizations to adapt swiftly to market changes and optimize their processes for better outcomes. Transforming Financial Reporting with Dynamic Dashboards Download Now 1.

Dashboards 52

Dashboards Reporting Operational Reporting Software 52

Jet Global

MAY 1, 2023

Section 2: Embedded Analytics: No Longer a Want but a Need Section 3: How to be Successful with Embedded Analytics Section 4: Embedded Analytics: Build versus Buy Section 5: Evaluating an Embedded Analytics Solution Section 6: Go-to-Market Best Practices Section 7: The Future of Embedded Analytics Section 1: What are Embedded Analytics?

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

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52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52