Smart Data Collective

APRIL 2, 2019

These massive storage pools of data are among the most non-traditional methods of data storage around and they came about as companies raced to embrace the trend of Big Data Analytics which was sweeping the world in the early 2010s. Big Data is, well…big.

Big Data 266

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Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. Building the right data model is an important part of your data strategy.

Data Modelling 84

Data Modelling Big Data Data Analytics Data Analytics 84

BizAcuity

MARCH 31, 2022

Combined, it has come to a point where data analytics is your safety net first, and business driver second. By 2025, 80% of organizations seeking to scale digital business will fail because they do not take a modern approach to data and analytics governance. Uncertain economic conditions. Source: Gartner Research).

Artificial Intelligence 130

Artificial Intelligence Data Analytics Data Analytics Predictive Analytics 130

Smart Data Collective

MAY 29, 2023

The Role of an Effective Analyst Data analysts are responsible for the harvesting, management, analysis, and interpretation of big data gathered. Skills Sets to Look For When entering into the hiring process for a data analyst there are a few skills that are recommended to look for when narrowing down the pool of options.

Big Data 262

Big Data Healthcare Data Modelling Data Analytics 262

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices.

Data Warehouse 264

Data Warehouse Data Quality Data Analytics Data Analytics 264

Sisense

OCTOBER 21, 2020

As a member of the data team, your role is complex and multifaceted, but one important way you support your colleagues across the company is by building and maintaining data models. Picking a direction for your data model. Think like a designer. However, just asking your users, “What do you want?”

Data Modelling 71

Data Modelling Embedded Analytics Design Thinking Big Data 71

Smart Data Collective

JUNE 16, 2022

A data warehouse extracts data from a variety of sources and formats, including text files, excel sheets, multimedia files, and so on. Types: HOLAP stands for Hybrid Online Analytical Processing. This provides both the ROLAP model’s data efficiency and the MOLAP model’s performance.

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Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

Big Data Data Analytics Data Analytics Supply Chain 52

Astera

MAY 30, 2024

What Is Data Analytics? Data analytics is the science of analyzing raw data to draw conclusions about it. The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. Data Mining : Sifting through data to find relevant information.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Astera

MAY 31, 2024

Data Science vs. Data Analytics Organizations increasingly use data to gain a competitive edge. Two key disciplines have emerged at the forefront of this approach: data science vs data analytics. In contrast, data science enables you to create data-driven algorithms to forecast future outcomes.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Astera

OCTOBER 7, 2022

The Rise of Unstructured Data Analytics. Until recently, enterprises solely relied on structured data to make business decisions — as conventional software couldn’t ingest, process, and extract the information from unstructured text mainly due to… the lack of structure. Why Is Unstructured Data Analytics Important?

Data Analytics 52

Data Analytics Data Analytics Documentation Customer Experience 52

Analysts Corner

JUNE 18, 2023

Python, Java, C#) Familiarity with data modeling and data warehousing concepts Understanding of data quality and data governance principles Experience with big data platforms and technologies (e.g., Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Sisense

JANUARY 15, 2021

This is one of the reasons we’ve seen the rise of data teams — they’ve grown beyond Silicon Valley startups and are finding homes in Fortune 500 companies. As data has become more massive, the technical skills needed to wrangle it have also increased. Situation #2: Established company creates a data team for deeper insights.

Skillset 75

Skillset Data Warehouse Data Modelling Business Intelligence 75

Insight Software

AUGUST 4, 2023

Providing valuable insights from data that moves the business forward in achieving its strategic objectives is one of the most valuable skills any FP&A or Operational Planning (OP) professional can possess. Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.

Data Analytics 52

Data Analytics Data Analytics Finance Visualization 52

Marutitech

DECEMBER 17, 2021

You must be wondering what the different predictive models are? What is predictive data modeling? Which predictive analytics algorithms are most helpful for them? This blog will help you answer these questions and understand the predictive analytics models and algorithms in detail.

Predictive Analytics 140

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Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! In The Future of Work , we explore how companies are transforming to stay competitive as global collaboration becomes vital.

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Sisense

JULY 24, 2019

Last, and still a very painful challenge for most users, is the familiarity with the underlying data and data model. NLQ is gaining traction in the big data analytics tools domain for its quick answers and ease of use. In other words, how the variables are named, and the granularity of their values.

Skillset 89

Skillset Big Data Data Modelling Data Analytics 89

Sisense

JUNE 12, 2019

Living in a World of Big Data. It all starts with the data. More than a decade ago, when the term Big Data emerged, companies started to invest heavily in the infrastructure to gather and store their data, realizing the potential future value of their data. Building a Better Tomorrow.

Artificial Intelligence 75

Artificial Intelligence Big Data Data Analytics Data Analytics 75

Astera

APRIL 27, 2023

The modern data stack (MDS) is a collection of tools for data integration that enable organizations to collect, process, store and analyze data. Being based on a well-integrated cloud platform, modern data stack offers scalability, efficiency, and proficiency in data handling.

Data Warehouse 52

Data Warehouse Big Data Data Analytics Data Analytics 52

Astera

MAY 25, 2023

Unlocking the Potential of Amazon Redshift Amazon Redshift is a powerful cloud-based data warehouse that enables quick and efficient processing and analysis of big data. Amazon Redshift can handle large volumes of data without sacrificing performance or scalability. These include dimensional models and data vaults.

Data Warehouse 52

Data Warehouse Data Modelling Banking Real-time Data 52

Whizlabs

DECEMBER 23, 2020

However, organizations also face the need for ideal infrastructure for the storage, analysis, and processing of large volumes of data. Apache Cassandra has been one of the prominent names in the field of big data analytics for quite some time. Read Now: How NoSQL is better for big data applications.

Big Data 52

Big Data Data Analytics Data Analytics Data Modelling 52

The BAWorld

APRIL 11, 2022

There’s never been a better time to broaden your data analytics knowledge. Still, if you’re considering getting a data analytics certification, you’ll want to know if it’s worth it. But which data analytics qualifications are the best? Skills Required to Become a Data Analyst.

IBM Maintenance 52

IBM Maintenance IBM cost IBM Support Data Analytics 52

The BAWorld

APRIL 11, 2022

There’s never been a better time to broaden your data analytics knowledge. Still, if you’re considering getting a data analyst certifications, you’ll want to know if it’s worth it. But which data analytics qualifications are the best? Skills Required to Become a Data Analyst.

IBM Maintenance 52

IBM Maintenance IBM cost IBM Support Data Analytics 52

Cprime

MAY 4, 2023

Key Data Integration Use Cases Let’s focus on the four primary use cases that require various data integration techniques: Data ingestion Data replication Data warehouse automation Big data integration Data Ingestion The data ingestion process involves moving data from a variety of sources to a storage location such as a data warehouse or data lake.

Data Warehouse 52

Data Warehouse Big Data Finance Data Quality 52

The BAWorld

SEPTEMBER 2, 2021

This is a classic example of structured data and can be efficiently managed through a database. Unstructured Data. Unstructured data has no definite structure or data model and is stored in its native format. of organizations are investing in big data. As per New Vantage, 97.2% Did You Know?

Big Data 52

Big Data Data Warehouse Data Visualization Visualization 52

Astera

AUGUST 22, 2023

Uncover hidden insights and possibilities with Generative AI capabilities and the new, cutting-edge data analytics and preparation add-ons We’re excited to announce the release of Astera 10.3—the the latest version of our enterprise-grade data management platform. Step Into the Future: Take Charge with Astera 10.3!

Innovation 52

Innovation Documentation Data Analytics Data Analytics 52

Astera

NOVEMBER 14, 2023

And consequently, having a constantly evolving architecture means you will have access to accurate, up-to-date data to fuel your analytics, allowing teams and departments to meet their respective goals.

Data Warehouse 52

Data Warehouse Agile Data Modelling Data Quality 52

Actian

MAY 21, 2019

The refinement process starts with the ingestion and aggregation of data from each of the source systems. This is often done in some sort of data warehouse. Once the data is in a common place, it must be merged and reconciled into a common data model – addressing, for example, duplication, gaps, time differences and conflicts.

Big Data 40

Big Data Data Warehouse Artificial Intelligence Digital Transformation 40

Astera

OCTOBER 27, 2023

Transitioning to a different cloud provider or adopting a multi-cloud strategy becomes complex, as the migration process may involve rewriting queries, adapting data models, and addressing compatibility issues. Dimensional Modeling or Data Vault Modeling? We've got both!

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Data Pine

MARCH 31, 2022

A data scientist has a similar role as the BI analyst, however, they do different things. While analysts focus on historical data to understand current business performance, scientists focus more on data modeling and prescriptive analysis. They can help a company forecast demand, or anticipate fraud.

Business Intelligence 95

Business Intelligence Business Intelligence Data Visualization Visualization 95

Astera

SEPTEMBER 20, 2024

NoSQL Databases: NoSQL databases are designed to handle large volumes of unstructured or semi-structured data. Unlike relational databases, they do not rely on a fixed schema, providing more flexibility in data modeling. This global presence ensures consistent and efficient data retrieval regardless of location.

Data Warehouse 40

Data Warehouse Cloud Computing E-Commerce Documentation 40

Whizlabs

APRIL 19, 2021

Michelle has more than 20 years of experience in the field of research in statistics, data analytics, consulting and market research. As a Chief Customer Officer, she is expert in cloud-based subscription models, automation and data analytics to drive customer adoption of software and reduce churn.

Cloud Computing 145

Cloud Computing IBM Support IBM Maintenance IBM cost 145

Astera

AUGUST 28, 2024

The concept of data analysis is as old as the data itself. Big data and the need for quickly analyzing large amounts of data have led to the development of various tools and platforms with a long list of features. Are your teams spending hours manually cleaning and preparing data for analysis?

IBM Support 40

IBM Support IBM Maintenance IBM cost Data Mining 40

Insight Software

MAY 1, 2023

Third-party data might include industry benchmarks, data feeds (such as weather and social media), and/or anonymized customer data. Four Approaches to Data Analytics The world of data analytics is constantly and quickly changing. Ideally, your primary data source should belong in this group.

Embedded Analytics 52

Embedded Analytics IBM Support IBM Maintenance IBM cost 52