Smart Data Collective

NOVEMBER 1, 2020

k-means Clustering – Document clustering, Data mining. In data mining, k-means clustering is used to classify observations into groups of related observations with no predefined relationships. Hidden Markov Model – Pattern Recognition, Bioinformatics, Data Analytics. Source ].

Machine Learning 131

Machine Learning Data mining Visualization Statistics 131

Smart Data Collective

SEPTEMBER 2, 2022

Operational data refers to the way the business runs, including shipping and logistics, and customer relationship management. Data has become very important for improving customer service. Use Big Data for Reputation Management. You need to use data mining to improve reptation management.

Big Data 116

Big Data Marketing Optimization Data mining 116

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. While third-party data can play a role in both optimization and conversions, it isn’t necessarily the most useful in the predictive analytics world.

Predictive Analytics 119

Predictive Analytics Analytics Predictive Modeling Data mining 119

Smart Data Collective

JUNE 14, 2022

There are a lot of important practices that you need to follow if you want to make sure that your program can properly carry out data analytics or data mining tasks. Common Programming Mistakes Data Developers Must Avoid. You will need to start by learning the right programming languages.

Data mining 90

Data mining Big Data Data Science Statistics 90

FineReport

JUNE 11, 2021

Business intelligence and analytics (BI&A) and the related field of big data analytics have emerged as an increasingly important area in the business communities. But if you are working in a company with complex business, I suggest you distinguish between business intelligence and data analytics. Definition.

Business Intelligence 98

Business Intelligence Analytics Dashboards Statistics 98

datapine

SEPTEMBER 27, 2022

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

Smart Data Collective

APRIL 8, 2020

Data warehouse, also known as a decision support database, refers to a central repository, which holds information derived from one or more data sources, such as transactional systems and relational databases. The data collected in the system may in the form of unstructured, semi-structured, or structured data.

Technology 132

Technology Data Warehouse Big Data Machine Learning 132

CIO Business Intelligence

MARCH 24, 2023

Whereas data governance is about the roles, responsibilities, and processes for ensuring accountability for and ownership of data assets, DAMA defines data management as “an overarching term that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

BizAcuity

OCTOBER 21, 2019

The key factor for the prosperity of the Hotel is service, online reviews & experience, using the information technology organizations are capturing the data to develop the latest techniques using data analytics to survive the competition. Decoding online reviews through analytics.

Analytics 73

Analytics Unstructured Data Data mining Structured Data 73

Smart Data Collective

FEBRUARY 28, 2022

Use Data Analytics to Craft the Perfect Social Media Management Strategy. Data analytics has made it a lot easier to manage your social media marketing strategies. You will be able to leverage analytics technology to see what strategies are performing the best. Big data is helping improve SEO strategies.

Big Data 97

Big Data Marketing Strategy Data-driven 97

FineReport

JUNE 11, 2021

Business intelligence and analytics (BI&A) and the related field of big data analytics have emerged as an increasingly important area in the business communities. But if you are working in a company with complex business, I suggest you distinguish between business intelligence and data analytics. Definition.

Business Intelligence 52

Business Intelligence Analytics Dashboards Statistics 52

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 57

Machine Learning Data Science Statistics Deep Learning 57

datapine

MAY 14, 2019

By acquiring a deep working understanding of data science and its many business intelligence branches, you stand to gain an all-important competitive edge that will help to position your business as a leader in its field. Hands down one of the best books for data science. It’s also one of the best books on data science around.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

BizAcuity

OCTOBER 21, 2019

The key factor for the prosperity of the Hotel is service, online reviews & experience, using the information technology organizations are capturing the data to develop the latest techniques using data analytics to survive the competition. DECODING ONLINE REVIEWS THROUGH ANALYTICS.

Analytics 40

Analytics Unstructured Data Data mining Structured Data 40

Sisense

MARCH 14, 2021

However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Sisense

APRIL 26, 2020

Companies and businesses focus a lot on data collection in order to make sure they can get valuable insights out of it. Understanding data structure is a key to unlocking its value. A data’s “structure” refers to a particular way of organizing and storing it in a database or warehouse so that it can be accessed and analyzed.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

erwin

JUNE 11, 2020

Data Intelligence is the analysis of multifaceted data to be used by companies to improve products and services offered and better support investments and business strategies in place. Data intelligence can encompass both internal and external business data and information. Transforming Industries with Data Intelligence.

Key Performance Indicator 103

Key Performance Indicator KPI Data-driven Machine Learning 103

Sisense

AUGUST 19, 2020

Disrupting Markets is your window into how companies have digitally transformed their businesses, shaken up their industries, and even changed the world through the use of data and analytics. The use of big data analytics and cloud computing has spiked phenomenally during the last decade. Ready to disrupt the market?

Big Data 52

Big Data Machine Learning Digital Transformation Marketing 52

datapine

JANUARY 24, 2021

This genie (who we’ll call Data Dan) embodies the idea of a perfect data analytics platform through his magic powers. Now, with Data Dan, you only get to ask him three questions. The questions to ask when analyzing data will be the framework, the lens, that allows you to focus on specific aspects of your business reality.

IT 317

IT Statistics KPI Data-driven 317

Sisense

AUGUST 11, 2019

BI lets you apply chosen metrics to potentially huge, unstructured datasets, and covers querying, data mining , online analytical processing ( OLAP ), and reporting as well as business performance monitoring, predictive and prescriptive analytics. Business Analytics is One Part of Business Intelligence.

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Smart Data Collective

DECEMBER 18, 2020

Another benefit of advances in data technology has to do with food and beverage labeling. Data analytics assists with everything from enhancing labeling software to extracting more data for compliance purposes. As IBM pointed out, this is one of the reasons that big data has improved food and beverage safety.

Data Analytics 117

Data Analytics Analytics Big Data Data mining 117

datapine

MARCH 31, 2022

To help you improve your business intelligence engineer resume, or as it’s sometimes referred to, ‘resume BI engineer’, you should explore this BI resume example for guidance that will help your application get noticed by potential employers. BI Project Manager. SAS BI: SAS can be considered the “mother” of all BI tools.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

BizAcuity

MARCH 31, 2022

Combined, it has come to a point where data analytics is your safety net first, and business driver second. With the massive influx of big data, several businesses use AI platforms to help save costs in a number of ways including automating certain procedures, speeding up key activities among others. Hope the article helped.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

CIO Business Intelligence

JANUARY 20, 2023

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Intelligence 141

Business Intelligence Dashboards Data mining OLAP 141

datapine

MARCH 25, 2019

What Is A Data Analysis Method? Data analysis method focuses on strategic approaches to taking raw data, mining for insights that are relevant to the business’s primary goals, and drilling down into this information to transform metrics, facts, and figures into initiatives that benefit improvement. Harvest your data.

Key Performance Indicator 217

Key Performance Indicator Statistics Visualization Big Data 217

IBM Big Data Hub

APRIL 15, 2024

This significantly reduces data integration time and expense, while also minimizing the potential for inaccuracies or data loss. Organizations can achieve a centralized perspective of their data, regardless of its storage source. This layer acts as a shield, hiding the complexities of data storage management.

Analytics 69

Analytics Optimization Data-driven Metrics 69

Smart Data Collective

DECEMBER 16, 2021

Some of the benefits of analytics actually have crossover with each other. For example, more companies than ever are using analytics to bolster their security. They are also using data analytics tools to help streamline many logistical processes and make sure supply chains operate more efficiently.

Analytics 124

Analytics Analytics Technologies Data mining Software 124

DataKitchen

OCTOBER 11, 2021

The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. First, a business analyst consolidates data from some public websites, an SFTP server and some downloaded email attachments, all into Excel.

Testing 157

Testing Metadata Dashboards Statistics 157

Grooper

AUGUST 19, 2019

These requirements include fluency in: Analytical models. Data science skills. Technology – i.e. data mining, predictive analytics, and statistics. Best practices for exploring collected data. Data is crucial to the success of business analytics. Machine Learning and Data Science.

Analytics 54

Analytics Machine Learning Data-driven Data Science 54

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. Big data analytics case study: SkullCandy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

IBM Big Data Hub

APRIL 10, 2023

In addition to this, network data is generated all the time and everybody has it – indeed, each CSP has an abundant unlimited data source that never stops. Therefore, data mining is the business of every CSP nowadays. We refer here to the ideas, internal gut feelings, etc.

Data mining 62

Data mining Data-driven Uncertainty Data Processing 62

Smart Data Collective

FEBRUARY 10, 2020

It is a good thing that big data makes it easier for people to conduct their own background checks. Here are some reasons using data analytics tools to find information on your own can be better than hiring a PI. There is another benefit of using big data for online dating. Identifying bogus job applications.

Big Data 91

Big Data Data mining Cost-Benefit Data Analytics 91

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

MAY 1, 2023

that gathers data from many sources. All of the above points to embedded analytics being not just the trendy route but the essential one. Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” It’s all about context.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52