Before you can create visuals and dashboards that convey useful information, you need to transform and prepare the underlying data. The range and complexity of data transformation steps required depends on the visuals you would like in your dashboard.
There’s a light at the end of the tunnel for IT pros who have been keeping a close eye on the job market. Plus, here are the skills that employers want in 2021.
Amazon EMR is a big data service offered by AWS to run Apache Spark and other open-source applications on AWS in a cost-effective manner. Amazon EMR Notebooks is a managed environment based on Jupyter Notebook that allows data scientists, analysts, and developers to prepare and visualize data, collaborate with peers, build applications, and perform interactive analysis using EMR clusters.
AWS Glue provides a serverless environment to prepare (extract and transform) and load large amounts of datasets from a variety of sources for analytics and data processing with Apache Spark ETL jobs. This posts discusses a new AWS Glue Spark runtime optimization that helps developers of Apache Spark applications and ETL jobs, big data architects, data engineers, and business analysts scale their data processing and batch jobs running on AWS Glue automatically.
This post discusses common use cases for Lambda stream processing and describes how to optimize the integration between Kinesis Data Streams and Lambda at high throughput with low system overhead and processing latencie
Across industries, big data has joined traditional, structured data as a mission-critical element. Here’s some advice for CIOs and big data leaders on how to
Today, Aspire Ventures is collaborating with AWS to open source anonymized crowd tracing data from the Clio GO pass system and make it available in the public AWS COVID-19 data lake.
Jupyter Notebook is pre-loaded with libraries needed to access the Data API, which you import when you use data from Amazon Redshift.
Although the augmented analytics vendors are continuously adding new capabilities to their products, there are some fundamental things that enterprises need to get right.
Augmented analytics tools also come with pre-built machine learning models to empower any user to do single click forecasts, identify trends and trend reversals, anomalies, outliers — tasks that in the past required involvement from professional data scientists.
Enterprise organizations have embraced the ideas behind advanced analytics technologies over the past several years, beginning with buzz words like big data and moving onto topics such as machine learning and artificial intelligence.
With that in mind, during its recent Gartner IT Symposium , the analyst firm unveiled its Top 10 Strategic Technology Trends in Data and Analytics, 2020, a list designed to take organizations “from crisis to opportunity,” as enterprises recover from the effects of the pandemic on business and IT initiatives.
IT Employment Trending Up; Data, Cybersecurity Skills in Demand There’s a light at the end of the tunnel for IT pros who have been keeping a close eye on the job market.
The four employment metrics tracked by CompTIA are IT sector (tech company) employment, IT occupation employment (IT jobs across all industry sectors), the unemployment rate for IT occupations, and employer job posting for new IT hires.
A new set of big data tools (spurred by the release of academic papers describing Google’s internal technology) gave data engineering experts the ability to collect and store this new data, making it available to expert users who could generate insights.
Unfortunately, even with this new data made available and accessible, most business users didn’t have the skills to generate insights
Weka has developed reference architectures (RAs) with leading object storage technology alliances, like Amazon Web Services (AWS), Cloudian, IBM, Seagate, Quantum, Scality , and others in Weka’s Technology Alliance Program, to deliver cost-efficient, cloud-native data storage solutions at any scale.
WekaFS provides the ease of managing petabytes of data in a single, unified namespace wherever in the pipeline the data is stored, while also delivering the best performance to accelerate artificial intelligence/machine learning (AI/ML), genomics research, high-performance computing (HPC), and high-performance data analytics (HPDA) workflows
Real-time insights into the rapidly evolving COVID-19 situation and its impact on all key stakeholders in the healthcare supply chain, including patients, physicians, and health systems, is a key asset in helping companies adapt based on local market dynamics and remain resilient to future disruptions
